This graduate-level textbook introduces fundamental concepts and methods in machine learning. It describes several important modern algorithms, provides the theoretical underpinnings of these algorithms, and illustrates key aspects for their application. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning fills the need for a general textbook that also offers theoretical details and an emphasis on proofs. Certain topics that are often treated with insufficient attention are discussed in more detail here; for example, entire chapters are devoted to regression, multi-class classification, and ranking. The first three chapters lay the theoretical foundation for what follows, but each remaining chapter is mostly self-contained. The appendix offers a concise probability review, a short introduction to convex optimization, tools for concentration bounds, and several basic properties of matrices and norms used in the book. The book is intended for graduate students and researchers in machine learning, statistics, and related areas; it can be used either as a textbook or as a reference text for a research seminar.
Cited By
- Jiang W, Goncalves J and Kostakos V (2024). Mobile Near-infrared Sensing—A Systematic Review on Devices, Data, Modeling, and Applications, ACM Computing Surveys, 56:8, (1-36), Online publication date: 31-Aug-2024.
- Shu S, Wang D, Yuan S, Wei H, Jiang J, Feng L and Zhang M (2024). Multiple-instance Learning from Triplet Comparison Bags, ACM Transactions on Knowledge Discovery from Data, 18:4, (1-18), Online publication date: 31-May-2024.
- Balcan M, Dick T, Sandholm T and Vitercik E (2024). Learning to Branch: Generalization Guarantees and Limits of Data-Independent Discretization, Journal of the ACM, 71:2, (1-73), Online publication date: 30-Apr-2024.
- Palma L, Diao Y and Liu A (2024). Efficient Version Space Algorithms for Human-in-the-loop Model Development, ACM Transactions on Knowledge Discovery from Data, 18:3, (1-49), Online publication date: 30-Apr-2024.
- Reeve H, Kabán A and Bootkrajang J (2024). Heterogeneous sets in dimensionality reduction and ensemble learning, Machine Language, 113:4, (1683-1704), Online publication date: 1-Apr-2024.
- Lyu H, Bai Y, Liang X, Das U, Shi C, Gong L, Li Y, Sun M, Ge M and Ma X FARPLS: A Feature-Augmented Robot Trajectory Preference Labeling System to Assist Human Labelers’ Preference Elicitation Proceedings of the 29th International Conference on Intelligent User Interfaces, (344-369)
- Chang L and Yao K (2024). Maximum k-Plex Computation: Theory and Practice, Proceedings of the ACM on Management of Data, 2:1, (1-26), Online publication date: 12-Mar-2024.
- Cornuéjols A (2024). Some thoughts about transfer learning. What role for the source domain?, International Journal of Approximate Reasoning, 166:C, Online publication date: 1-Mar-2024.
- Yang X, Wang Y, Liu Y, Wen Y, Meng L, Zhou S, Liu X and Zhu E (2024). Mixed Graph Contrastive Network for Semi-Supervised Node Classification, ACM Transactions on Knowledge Discovery from Data, 0:0
- Wang F, Han Z and Yin Y (2024). BIAS, Knowledge-Based Systems, 284:C, Online publication date: 25-Jan-2024.
- Petersen P and Sepliarskaia A (2024). VC dimensions of group convolutional neural networks, Neural Networks, 169:C, (462-474), Online publication date: 1-Jan-2024.
- Fu X, Shao M, Li S and Yang L Active Few-shot Learning For RouteNet-Fermi Proceedings of the 2nd on Graph Neural Networking Workshop 2023, (19-24)
- Xu S, Zhang S, Liu J, Zhuang B, Wang Y and Tan M (2023). Generative Data Free Model Quantization With Knowledge Matching for Classification, IEEE Transactions on Circuits and Systems for Video Technology, 33:12, (7296-7309), Online publication date: 1-Dec-2023.
- Guan X and Terada Y (2023). Sparse kernel k-means for high-dimensional data, Pattern Recognition, 144:C, Online publication date: 1-Dec-2023.
- Zhang Y, Lu J, Zhang H, Huang Z, Briso-Rodríguez C and Zhang L (2023). Experimental study on low-altitude UAV-to-ground propagation characteristics in campus environment, Computer Networks: The International Journal of Computer and Telecommunications Networking, 237:C, Online publication date: 1-Dec-2023.
- Kaisar T, Zaman K and Khasawneh M (2023). A new approach to probabilistic classification based on Gaussian process and support vector machine, Computers and Industrial Engineering, 186:C, Online publication date: 1-Dec-2023.
- Kassa A, Kitaw D, Stache U, Beshah B and Degefu G (2023). Artificial intelligence techniques for enhancing supply chain resilience, Computers and Industrial Engineering, 186:C, Online publication date: 1-Dec-2023.
- Feng L, Shu S, Cao Y, Tao L, Wei H, Xiang T, An B and Niu G (2023). Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity, IEEE Transactions on Knowledge and Data Engineering, 35:11, (11599-11609), Online publication date: 1-Nov-2023.
- Moscato V, Postiglione M and Sperlí G (2023). Few-shot Named Entity Recognition: Definition, Taxonomy and Research Directions, ACM Transactions on Intelligent Systems and Technology, 14:5, (1-46), Online publication date: 31-Oct-2023.
- Pham H, Dai Z, Ghiasi G, Kawaguchi K, Liu H, Yu A, Yu J, Chen Y, Luong M, Wu Y, Tan M and Le Q (2023). Combined scaling for zero-shot transfer learning, Neurocomputing, 555:C, Online publication date: 28-Oct-2023.
- Song Z, Chen J, Zhou S, Shi Q, Feng Y, Chen C and Wang C CDR: Conservative Doubly Robust Learning for Debiased Recommendation Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, (2321-2330)
- Huang M, Zhao Y, Wang Y, Wahab F, Sun Y and Chen C (2023). Multi-graph multi-label learning with novel and missing labels, Knowledge-Based Systems, 276:C, Online publication date: 27-Sep-2023.
- Kanamori K Learning Locally Interpretable Rule Ensemble Machine Learning and Knowledge Discovery in Databases: Research Track, (360-377)
- Mozzhechkov V (2023). Static Feedback Design in Linear Discrete-Time Control Systems Based on Training Examples, Automation and Remote Control, 84:9, (947-955), Online publication date: 1-Sep-2023.
- Shi L, Tan J, Wang J, Li Q, Lu L and Chen B (2023). Robust kernel adaptive filtering for nonlinear time series prediction, Signal Processing, 210:C, Online publication date: 1-Sep-2023.
- Wei M, Zhou Y, Li Z and Xu X (2023). Class-imbalanced complementary-label learning via weighted loss, Neural Networks, 166:C, (555-565), Online publication date: 1-Sep-2023.
- Hajiani M and Seyfe B (2023). From oracle generalization bound toward empirical inequality, Information Sciences: an International Journal, 642:C, Online publication date: 1-Sep-2023.
- Popescu M, Grama L and Rusu C (2023). An algorithm for training a class of polynomial models, Digital Signal Processing, 141:C, Online publication date: 1-Sep-2023.
- Chen H, He F, Lei S and Tao D (2023). Spectral complexity-scaled generalisation bound of complex-valued neural networks, Artificial Intelligence, 322:C, Online publication date: 1-Sep-2023.
- Li H, Zheng C, Wu P, Kuang K, Liu Y and Cui P Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (1235-1247)
- Wu H, Shi W, Zhang C and Gu B Self-Adaptive Perturbation Radii for Adversarial Training Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (2570-2581)
- Pellegrina L Efficient Centrality Maximization with Rademacher Averages Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (1872-1884)
- Ansari M, Pal K, Govil P, Govil M, Chaurasia N, Vidyarthi A and Alharbi M (2023). Identification of vulnerable selfish peer in P2P network using nature-inspired optimization techniques, Physical Communication, 59:C, Online publication date: 1-Aug-2023.
- Zhou Y, Lu M, Liu X, Che Z, Xu Z, Tang J, Zhang Y, Peng Y and Peng Y (2023). Distributional generative adversarial imitation learning with reproducing kernel generalization, Neural Networks, 165:C, (43-59), Online publication date: 1-Aug-2023.
- Park J, Choi J, Nah S and Kim D (2023). Distributional and hierarchical reinforcement learning for physical systems with noisy state observations and exogenous perturbations, Engineering Applications of Artificial Intelligence, 123:PC, Online publication date: 1-Aug-2023.
- Aliwi M, Demirci S and Aslan S (2023). Difference-based firefly programming for symbolic regression problems, Computer Standards & Interfaces, 86:C, Online publication date: 1-Aug-2023.
- Lei Y, Yang T, Ying Y and Zhou D Generalization analysis for contrastive representation learning Proceedings of the 40th International Conference on Machine Learning, (19200-19227)
- Yang Z, He X, Zhang J, Wu J, Xin X, Chen J and Wang X A Generic Learning Framework for Sequential Recommendation with Distribution Shifts Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, (331-340)
- Qi D and Harlim J (2023). A data-driven statistical-stochastic surrogate modeling strategy for complex nonlinear non-stationary dynamics, Journal of Computational Physics, 485:C, Online publication date: 15-Jul-2023.
- Hafez-Kolahi H, Moniri B and Kasaei S (2023). Information-Theoretic Analysis of Minimax Excess Risk, IEEE Transactions on Information Theory, 69:7, (4659-4674), Online publication date: 1-Jul-2023.
- Siegel J, Hong Q, Jin X, Hao W and Xu J (2023). Greedy training algorithms for neural networks and applications to PDEs, Journal of Computational Physics, 484:C, Online publication date: 1-Jul-2023.
- Hu W, Li X, Li C, Li R, Jiang T, Sun H, Huang X, Grzegorzek M and Li X (2023). A state-of-the-art survey of artificial neural networks for Whole-slide Image analysis, Computers in Biology and Medicine, 161:C, Online publication date: 1-Jul-2023.
- Geerts F A Query Language Perspective on Graph Learning Proceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, (373-379)
- Zhu J, Liu C, Wang P, Zhao X, Lin Z and Shao J Confidence Ranking for CTR Prediction Companion Proceedings of the ACM Web Conference 2023, (437-441)
- Song D, Wang Z, Huang Y, Ma L and Zhang T DeepLens: Interactive Out-of-distribution Data Detection in NLP Models Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, (1-17)
- Mey A and Loog M (2023). Improved Generalization in Semi-Supervised Learning: A Survey of Theoretical Results, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45:4, (4747-4767), Online publication date: 1-Apr-2023.
- Cerdà-Alabern L, Iuhasz G and Gemmi G (2023). Anomaly detection for fault detection in wireless community networks using machine learning, Computer Communications, 202:C, (191-203), Online publication date: 15-Mar-2023.
- Mandl C and Minner S (2023). Data-Driven Optimization for Commodity Procurement Under Price Uncertainty, Manufacturing & Service Operations Management, 25:2, (371-390), Online publication date: 1-Mar-2023.
- Ding X, Wang Y, Xu Z, Wang Z and Welch W (2023). Distilling and transferring knowledge via cGAN-generated samples for image classification and regression, Expert Systems with Applications: An International Journal, 213:PB, Online publication date: 1-Mar-2023.
- Albano A, Sciandra M and Plaia A (2023). A weighted distance-based approach with boosted decision trees for label ranking, Expert Systems with Applications: An International Journal, 213:PB, Online publication date: 1-Mar-2023.
- McDermott E, Metsomaa J, Belardinelli P, Grosse-Wentrup M, Ziemann U and Zrenner C (2023). Predicting motor behavior: an efficient EEG signal processing pipeline to detect brain states with potential therapeutic relevance for VR-based neurorehabilitation, Virtual Reality, 27:1, (347-369), Online publication date: 1-Mar-2023.
- Fang K, Liu F, Huang X and Yang J (2023). End-to-end kernel learning via generative random Fourier features, Pattern Recognition, 134:C, Online publication date: 1-Feb-2023.
- Petrović A, Nikolić M, Jovanović M and Delibašić B (2023). Gaussian conditional random fields for classification, Expert Systems with Applications: An International Journal, 212:C, Online publication date: 1-Feb-2023.
- Ding X, Wang Y, Wang Z and Welch W (2023). Efficient subsampling of realistic images from GANs conditional on a class or a continuous variable, Neurocomputing, 517:C, (188-200), Online publication date: 14-Jan-2023.
- Li Z, Li G, Li T, Liu S and Gao W (2023). Semantic Point Cloud Upsampling, IEEE Transactions on Multimedia, 25, (3432-3442), Online publication date: 1-Jan-2023.
- Luo Y, Wong Y, Kankanhalli M and Zhao Q (2023). Learning to Minimize the Remainder in Supervised Learning, IEEE Transactions on Multimedia, 25, (1738-1748), Online publication date: 1-Jan-2023.
- Wei C, Wang Z, Yuan J, Li C and Chen S (2023). Time-frequency based multi-task learning for semi-supervised time series classification, Information Sciences: an International Journal, 619:C, (762-780), Online publication date: 1-Jan-2023.
- Tian H, Song K, Li S, Ma S, Xu J and Yan Y (2023). Data-driven robotic visual grasping detection for unknown objects, Expert Systems with Applications: An International Journal, 211:C, Online publication date: 1-Jan-2023.
- Dang Y, Zhang Y and Wang J (2023). A novel multivariate grey model for forecasting periodic oscillation time series, Expert Systems with Applications: An International Journal, 211:C, Online publication date: 1-Jan-2023.
- Lee S, Moon W, Lee J and Sundar S (2023). When the machine learns from users, is it helping or snooping?, Computers in Human Behavior, 138:C, Online publication date: 1-Jan-2023.
- Petrović A, Radovanović S, Nikolić M, Delibašić B and Jovanović M (2023). Structured prediction of sparse dependent variables for traffic state estimation in large-scale networks, Applied Soft Computing, 133:C, Online publication date: 1-Jan-2023.
- de Lima A, da Silva M and Vignatti A (2022). Percolation centrality via Rademacher Complexity, Discrete Applied Mathematics, 323:C, (201-216), Online publication date: 31-Dec-2022.
- Banjac G and Lygeros J A Data-Driven Policy Iteration Scheme based on Linear Programming 2019 IEEE 58th Conference on Decision and Control (CDC), (816-821)
- Gzar D, Mahmood A and Al-Adilee M (2022). Recent trends of smart agricultural systems based on Internet of Things technology, Computers and Electrical Engineering, 104:PA, Online publication date: 1-Dec-2022.
- Shao H, Xu Q, Yang Z, Bao S and Huang Q Asymptotically unbiased instance-wise regularized partial AUC optimization Proceedings of the 36th International Conference on Neural Information Processing Systems, (38667-38679)
- Gourdeau P, Kanade V, Kwiatkowska M and Worrell J When are local queries useful for robust learning? Proceedings of the 36th International Conference on Neural Information Processing Systems, (33920-33933)
- Larsen K and Ritzert M Optimal weak to strong learning Proceedings of the 36th International Conference on Neural Information Processing Systems, (32830-32841)
- Balcan M, Khodak M, Sharma D and Talwalkar A Provably tuning the ElasticNet across instances Proceedings of the 36th International Conference on Neural Information Processing Systems, (27769-27782)
- Wang Z, Xu Q, Yang Z, He Y, Cao X and Huang Q OpenAUC Proceedings of the 36th International Conference on Neural Information Processing Systems, (25033-25045)
- Nishino M, Nakamura K and Yasuda N Generalization analysis on learning with a concurrent verifier Proceedings of the 36th International Conference on Neural Information Processing Systems, (4177-4188)
- Bao S, Xu Q, Yang Z, He Y, Cao X and Huang Q The minority matters Proceedings of the 36th International Conference on Neural Information Processing Systems, (2451-2464)
- Freitas L and Lelli V Using Machine Learning on Testing IoT Applications: a systematic mapping Proceedings of the Brazilian Symposium on Multimedia and the Web, (348-358)
- de Lima A, da Silva M and Vignatti A Estimating the Clustering Coefficient Using Sample Complexity Analysis LATIN 2022: Theoretical Informatics, (328-341)
- Yoo J, Yoo I, Youn I, Kim S, Yu R, Kim K, Kim K and Lee S (2022). Residual one-dimensional convolutional neural network for neuromuscular disorder classification from needle electromyography signals with explainability, Computer Methods and Programs in Biomedicine, 226:C, Online publication date: 1-Nov-2022.
- Yuan M, Zhang L, He F, Tong X and Li X InFi Proceedings of the 28th Annual International Conference on Mobile Computing And Networking, (228-241)
- Wang Z, Xu Q, Ma K, Cao X and Huang Q Confederated Learning: Going Beyond Centralization Proceedings of the 30th ACM International Conference on Multimedia, (2939-2947)
- Zhang M, Ren Y, Wang Z and Yuan C Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Proceedings of the 30th ACM International Conference on Multimedia, (4635-4644)
- Xu T, Li Z and Yu Y (2022). Error Bounds of Imitating Policies and Environments for Reinforcement Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 44:10_Part_2, (6968-6980), Online publication date: 1-Oct-2022.
- Lamb A, Verma V, Kawaguchi K, Matyasko A, Khosla S, Kannala J and Bengio Y (2022). Interpolated Adversarial Training, Neural Networks, 154:C, (218-233), Online publication date: 1-Oct-2022.
- Himeur Y, Rimal B, Tiwary A and Amira A (2022). Using artificial intelligence and data fusion for environmental monitoring, Information Fusion, 86:C, (44-75), Online publication date: 1-Oct-2022.
- Emakhu J, Monplaisir L, Aguwa C, Arslanturk S, Masoud S, Nassereddine H, Hamam M and Miller J (2022). Acute coronary syndrome prediction in emergency care, Computer Methods and Programs in Biomedicine, 225:C, Online publication date: 1-Oct-2022.
- Kang M, Hovav A, Lee E, Um S and Kim H (2022). Development of methods for identifying an appropriate benchmarking peer to establish information security policy, Expert Systems with Applications: An International Journal, 201:C, Online publication date: 1-Sep-2022.
- He R, Han Z and Yin Y (2022). Towards safe and robust weakly-supervised anomaly detection under subpopulation shift, Knowledge-Based Systems, 250:C, Online publication date: 17-Aug-2022.
- Geng Y, Liu Y, Lu Y, Shen C and Shi L (2022). Reinforcement learning explains various conditional cooperation, Applied Mathematics and Computation, 427:C, Online publication date: 15-Aug-2022.
- Yan Y, Niu C, Gu R, Wu F, Tang S, Hua L, Lyu C and Chen G On-Device Learning for Model Personalization with Large-Scale Cloud-Coordinated Domain Adaption Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (2180-2190)
- Ding S, Wu P, Feng F, Wang Y, He X, Liao Y and Zhang Y Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (305-315)
- Rehman A, Naz S and Razzak I (2022). Leveraging big data analytics in healthcare enhancement: trends, challenges and opportunities, Multimedia Systems, 28:4, (1339-1371), Online publication date: 1-Aug-2022.
- Özbay Karakuş M and Er O (2022). A comparative study on prediction of survival event of heart failure patients using machine learning algorithms, Neural Computing and Applications, 34:16, (13895-13908), Online publication date: 1-Aug-2022.
- Lyu S, Wang L and Zhou Z (2022). Improving generalization of deep neural networks by leveraging margin distribution, Neural Networks, 151:C, (48-60), Online publication date: 1-Jul-2022.
- McDermott T, Robson J, Winters N and Malmberg L Mapping the Changing Landscape of Child-Computer Interaction Research Through Correlated Topic Modelling Proceedings of the 21st Annual ACM Interaction Design and Children Conference, (82-97)
- Bharadwaja H. S, Bansal M and Murthy C Approximate Set Identification: PAC Analysis for Group Testing 2022 IEEE International Symposium on Information Theory (ISIT), (2237-2242)
- Xia S and Yang Y (2022). An iterative model-free feature screening procedure, Knowledge-Based Systems, 246:C, Online publication date: 21-Jun-2022.
- Shi T and Wang J (2022). Exploiting Data Mining for Fast Inter Prediction Mode Decision in HEVC, Mobile Networks and Applications, 27:3, (1092-1100), Online publication date: 1-Jun-2022.
- Li P, Yang J and Ren S (2022). Expert-Calibrated Learning for Online Optimization with Switching Costs, Proceedings of the ACM on Measurement and Analysis of Computing Systems, 6:2, (1-35), Online publication date: 26-May-2022.
- Böhme M Statistical reasoning about programs Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results, (76-80)
- Zhu H and Bayley I (2022). Discovering boundary values of feature-based machine learning classifiers through exploratory datamorphic testing, Journal of Systems and Software, 187:C, Online publication date: 1-May-2022.
- Tan C, Lee V and Salehi M (2022). Information resources estimation for accurate distribution-based concept drift detection, Information Processing and Management: an International Journal, 59:3, Online publication date: 1-May-2022.
- Xie R and Wang S (2022). A wide interpretable Gaussian Takagi–Sugeno–Kang fuzzy classifier and its incremental learning, Knowledge-Based Systems, 241:C, Online publication date: 6-Apr-2022.
- Bonnici I, Gouaïch A and Michel F (2021). Input addition and deletion in reinforcement: towards protean learning, Autonomous Agents and Multi-Agent Systems, 36:1, Online publication date: 1-Apr-2022.
- Figalist I, Elsner C, Bosch J and Olsson H (2022). Breaking the vicious circle, Journal of Systems and Software, 184:C, Online publication date: 1-Feb-2022.
- Zhang J, Harman M, Ma L and Liu Y (2022). Machine Learning Testing: Survey, Landscapes and Horizons, IEEE Transactions on Software Engineering, 48:1, (1-36), Online publication date: 1-Jan-2022.
- Yang Y, Li Z and Wang Y (2022). On the capacity of deep generative networks for approximating distributions, Neural Networks, 145:C, (144-154), Online publication date: 1-Jan-2022.
- Verma V, Kawaguchi K, Lamb A, Kannala J, Solin A, Bengio Y and Lopez-Paz D (2022). Interpolation consistency training for semi-supervised learning, Neural Networks, 145:C, (90-106), Online publication date: 1-Jan-2022.
- Hayashi K and Ohsaki M (2023). Graph-based reinforcement learning for discrete cross-section optimization of planar steel frames, Advanced Engineering Informatics, 51:C, Online publication date: 1-Jan-2022.
- Fernández-Edreira D, Liñares-Blanco J and Fernandez-Lozano C (2021). Machine Learning analysis of the human infant gut microbiome identifies influential species in type 1 diabetes, Expert Systems with Applications: An International Journal, 185:C, Online publication date: 15-Dec-2021.
- Lee W, Ko H, Byun J, Yoon T and Lee J (2021). Fair Clustering with Fair Correspondence Distribution, Information Sciences: an International Journal, 581:C, (155-178), Online publication date: 1-Dec-2021.
- Gottlieb L, Kaufman E and Kontorovich A (2021). Apportioned margin approach for cost sensitive large margin classifiers, Annals of Mathematics and Artificial Intelligence, 89:12, (1215-1235), Online publication date: 1-Dec-2021.
- Negrini E, Citti G and Capogna L (2022). System identification through Lipschitz regularized deep neural networks, Journal of Computational Physics, 444:C, Online publication date: 1-Nov-2021.
- Zhou X and Qiu D (2021). Blind quantum machine learning based on quantum circuit model, Quantum Information Processing, 20:11, Online publication date: 1-Nov-2021.
- Wang W, Cao Y, Zhang J, He F, Zha Z, Wen Y and Tao D Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers Proceedings of the 29th ACM International Conference on Multimedia, (1730-1738)
- Li Z, Li G, Li T, Liu S and Gao W Information-Growth Attention Network for Image Super-Resolution Proceedings of the 29th ACM International Conference on Multimedia, (544-552)
- Razi A, Kim S, Alsoubai A, Stringhini G, Solorio T, De Choudhury M and Wisniewski P (2021). A Human-Centered Systematic Literature Review of the Computational Approaches for Online Sexual Risk Detection, Proceedings of the ACM on Human-Computer Interaction, 5:CSCW2, (1-38), Online publication date: 13-Oct-2021.
- Li L, Zheng N and Wang F (2021). A Theoretical Foundation of Intelligence Testing and Its Application for Intelligent Vehicles, IEEE Transactions on Intelligent Transportation Systems, 22:10, (6297-6306), Online publication date: 1-Oct-2021.
- Sakai T Source Hypothesis Transfer for Zero-Shot Domain Adaptation Machine Learning and Knowledge Discovery in Databases. Research Track, (570-586)
- Caro-Martínez M, Jiménez-Díaz G and Recio-García J (2021). Conceptual Modeling of Explainable Recommender Systems, Journal of Artificial Intelligence Research, 71, (557-589), Online publication date: 10-Sep-2021.
- Dhar S, Guo J, Liu J, Tripathi S, Kurup U and Shah M (2021). A Survey of On-Device Machine Learning, ACM Transactions on Internet of Things, 2:3, (1-49), Online publication date: 31-Aug-2021.
- Yıldırım M, Okay F and Özdemir S (2021). Big data analytics for default prediction using graph theory, Expert Systems with Applications: An International Journal, 176:C, Online publication date: 15-Aug-2021.
- Betlei A, Diemert E and Amini M Uplift Modeling with Generalization Guarantees Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, (55-65)
- Wen Z, Zhou Z, Liu H, He B, Li X and Chen J Enhancing SVMs with Problem Context Aware Pipeline Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, (1821-1829)
- Jain P, Pamula R and Srivastava G (2021). A systematic literature review on machine learning applications for consumer sentiment analysis using online reviews, Computer Science Review, 41:C, Online publication date: 1-Aug-2021.
- Keswani V, Lease M and Kenthapadi K Towards Unbiased and Accurate Deferral to Multiple Experts Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, (154-165)
- Frongillo R, Gomez R, Thilagar A and Waggoner B Efficient Competitions and Online Learning with Strategic Forecasters Proceedings of the 22nd ACM Conference on Economics and Computation, (479-496)
- Ma G, Liu F, Zhang G and Lu J Learning from Imprecise Observations: An Estimation Error Bound based on Fuzzy Random Variables 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), (1-8)
- Coey D, Larsen B, Sweeney K and Waisman C (2021). Scalable Optimal Online Auctions, Marketing Science, 40:4, (593-618), Online publication date: 1-Jul-2021.
- Chen C, Watabe M, Shiba K, Sogabe M, Sakamoto K and Sogabe T (2021). On the Expressibility and Overfitting of Quantum Circuit Learning, ACM Transactions on Quantum Computing, 2:2, (1-24), Online publication date: 1-Jul-2021.
- Tao Y and Wang Y New Algorithms for Monotone Classification Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, (260-272)
- García-Domínguez M, Domínguez C, Heras J, Mata E and Pascual V (2021). UFOD, Pattern Recognition Letters, 145:C, (135-140), Online publication date: 1-May-2021.
- Amornbunchornvej C, Surasvadi N, Plangprasopchok A and Thajchayapong S (2021). Identifying Linear Models in Multi-Resolution Population Data Using Minimum Description Length Principle to Predict Household Income, ACM Transactions on Knowledge Discovery from Data, 15:2, (1-30), Online publication date: 30-Apr-2021.
- Kocak M, Ramirez D, Erkip E and Shasha D (2021). SafePredict: A Meta-Algorithm for Machine Learning That Uses Refusals to Guarantee Correctness, IEEE Transactions on Pattern Analysis and Machine Intelligence, 43:2, (663-678), Online publication date: 1-Feb-2021.
- Tassarotti J, Vajjha K, Banerjee A and Tristan J A formal proof of PAC learnability for decision stumps Proceedings of the 10th ACM SIGPLAN International Conference on Certified Programs and Proofs, (5-17)
- Li J, Lu K, Huang Z and Shen H (2020). On Both Cold-Start and Long-Tail Recommendation with Social Data, IEEE Transactions on Knowledge and Data Engineering, 33:1, (194-208), Online publication date: 1-Jan-2021.
- Beil D and Theissler A Cluster-clean-label Proceedings of the 13th International Symposium on Visual Information Communication and Interaction, (1-8)
- Lei Y, Ledent A and Kloft M Sharper generalization bounds for pairwise learning Proceedings of the 34th International Conference on Neural Information Processing Systems, (21236-21246)
- Cortes C, Gonzalvo J, Mohri M and Storcheus D Agnostic learning with multiple objectives Proceedings of the 34th International Conference on Neural Information Processing Systems, (20485-20495)
- Abbe E and Sandon C On the universality of deep learning Proceedings of the 34th International Conference on Neural Information Processing Systems, (20061-20072)
- Suzuki T Generalization bound of globally optimal non-convex neural network training Proceedings of the 34th International Conference on Neural Information Processing Systems, (19224-19237)
- Hu W, Xiao L, Adlam B and Pennington J The surprising simplicity of the early-time learning dynamics of neural networks Proceedings of the 34th International Conference on Neural Information Processing Systems, (17116-17128)
- Xu T, Li Z and Yu Y Error bounds of imitating policies and environments Proceedings of the 34th International Conference on Neural Information Processing Systems, (15737-15749)
- Hammoudeh Z and Lowd D Learning from positive and unlabeled data with arbitrary positive shift Proceedings of the 34th International Conference on Neural Information Processing Systems, (13088-13099)
- Zhang Y, Zhao P, Ma L and Zhou Z An unbiased risk estimator for learning with augmented classes Proceedings of the 34th International Conference on Neural Information Processing Systems, (10247-10258)
- Dong M, Yang X, Zhu R, Wang Y and Xue J Generalization bound of gradient descent for non-convex metric learning Proceedings of the 34th International Conference on Neural Information Processing Systems, (9794-9805)
- Zhou L, Sutherland D and Srebro N On uniform convergence and low-norm interpolation learning Proceedings of the 34th International Conference on Neural Information Processing Systems, (6867-6877)
- Cohen D, Kontorovich A and Wolfer G Learning discrete distributions with infinite support Proceedings of the 34th International Conference on Neural Information Processing Systems, (3942-3951)
- Shen C, Xue W, Zhang L and Wang B (2020). An Active-Set Proximal-Newton Algorithm for Regularized Optimization Problems with Box Constraints, Journal of Scientific Computing, 85:3, Online publication date: 1-Dec-2020.
- Guermeur Y (2018). Rademacher complexity of margin multi-category classifiers, Neural Computing and Applications, 32:24, (17995-18008), Online publication date: 1-Dec-2020.
- Usman M, Jan M, He X and Chen J (2019). A Survey on Representation Learning Efforts in Cybersecurity Domain, ACM Computing Surveys, 52:6, (1-28), Online publication date: 30-Nov-2020.
- Santoso A and Felderer M (2019). Specification-driven predictive business process monitoring, Software and Systems Modeling (SoSyM), 19:6, (1307-1343), Online publication date: 1-Nov-2020.
- Raboudi K and Saci A Machine learning for optimized buildings morphosis Proceedings of the 2nd International Conference on Digital Tools & Uses Congress, (1-5)
- Boccia M, Sforza A and Sterle C (2020). Simple Pattern Minimality Problems, INFORMS Journal on Computing, 32:4, (1049-1060), Online publication date: 1-Oct-2020.
- Filisbino T, Giraldi G and Thomaz C (2020). Support vector machine ensembles for discriminant analysis for ranking principal components, Multimedia Tools and Applications, 79:35-36, (25277-25313), Online publication date: 1-Sep-2020.
- Belkacem S, Boukhalfa K and Boussaid O (2019). Expertise-aware news feed updates recommendation: a random forest approach, Cluster Computing, 23:3, (2375-2388), Online publication date: 1-Sep-2020.
- Madhyastha M, Li G, Strnadová-Neeley V, Browne J, Vogelstein J, Burns R and Priebe C Geodesic Forests Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, (513-523)
- Tao Y and Lu S From Online to Non-i.i.d. Batch Learning Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, (328-337)
- Luo Y, Wong Y, Kankanhalli M and Zhao Q n-Reference Transfer Learning for Saliency Prediction Computer Vision – ECCV 2020, (502-519)
- Suehiro D, Hatano K, Takimoto E, Yamamoto S, Bannai K and Takeda A (2020). Theory and Algorithms for Shapelet-Based Multiple-Instance Learning, Neural Computation, 32:8, (1580-1613), Online publication date: 1-Aug-2020.
- Eke C, Norman A, Liyana Shuib and Nweke H (2019). Sarcasm identification in textual data: systematic review, research challenges and open directions, Artificial Intelligence Review, 53:6, (4215-4258), Online publication date: 1-Aug-2020.
- Xu Z, Dan C, Khim J and Ravikumar P Class-weighted classification Proceedings of the 37th International Conference on Machine Learning, (10544-10554)
- Wen J, Dai B, Li L and Schuurmans D Batch stationary distribution estimation Proceedings of the 37th International Conference on Machine Learning, (10203-10213)
- Uehara M, Huang J and Jiang N Minimax weight and Q-function learning for off-policy evaluation Proceedings of the 37th International Conference on Machine Learning, (9659-9668)
- Teshima T, Sato I and Sugiyama M Few-shot domain adaptation by causal mechanism transfer Proceedings of the 37th International Conference on Machine Learning, (9458-9469)
- Scetbon M and Harchaoui Z Harmonic decompositions of convolutional networks Proceedings of the 37th International Conference on Machine Learning, (8522-8532)
- Reeve H and Kabán A Optimistic bounds for multi-output prediction Proceedings of the 37th International Conference on Machine Learning, (8030-8040)
- Lv J, Xu M, Feng L, Niu G, Geng X and Sugiyama M Progressive identification of true labels for partial-label learning Proceedings of the 37th International Conference on Machine Learning, (6500-6510)
- Garg V, Jegelka S and Jaakkola T Generalization and representational limits of graph neural networks Proceedings of the 37th International Conference on Machine Learning, (3419-3430)
- Balcan M, Sandholm T and Vitercik E Refined bounds for algorithm configuration Proceedings of the 37th International Conference on Machine Learning, (580-590)
- Feldbacher-Escamilla C and Schurz G (2019). Optimal probability aggregation based on generalized brier scoring, Annals of Mathematics and Artificial Intelligence, 88:7, (717-734), Online publication date: 1-Jul-2020.
- Popescu C, Grama L and Rusu C On the use of positive definite symmetric kernels for summary extraction 2020 13th International Conference on Communications (COMM), (335-340)
- Kumar P. K, Langton P and Gatterbauer W Factorized Graph Representations for Semi-Supervised Learning from Sparse Data Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, (1383-1398)
- Sindhgatta R, ter Hofstede A and Ghose A Resource-Based Adaptive Robotic Process Automation Advanced Information Systems Engineering, (451-466)
- Shi W, Luo Y and Wu G (2020). On general matrix exponential discriminant analysis methods for high dimensionality reduction, Calcolo: a quarterly on numerical analysis and theory of computation, 57:2, Online publication date: 3-Jun-2020.
- Zhitomirsky-Geffet M, Bergman O and Hilel S (2020). Towards a wider perspective in the social sciences using a network of variables based on thousands of results, Scientometrics, 123:3, (1385-1406), Online publication date: 1-Jun-2020.
- Usman M, Jan M, He X and Chen J (2019). A Survey on Big Multimedia Data Processing and Management in Smart Cities, ACM Computing Surveys, 52:3, (1-29), Online publication date: 31-May-2020.
- Gu R, Yang Z and Ji Y (2020). Machine learning for intelligent optical networks, Journal of Network and Computer Applications, 157:C, Online publication date: 1-May-2020.
- Viering T, Mey A and Loog M Making Learners (More) Monotone Advances in Intelligent Data Analysis XVIII, (535-547)
- Mey A, Viering T and Loog M A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization Advances in Intelligent Data Analysis XVIII, (326-338)
- Cornuéjols A, Murena P and Olivier R Transfer Learning by Learning Projections from Target to Source Advances in Intelligent Data Analysis XVIII, (119-131)
- Bertsimas D and Kallus N (2020). From Predictive to Prescriptive Analytics, Management Science, 66:3, (1025-1044), Online publication date: 1-Mar-2020.
- Hu Q, de F. Souza L, Holanda G, Alves S, dos S. Silva F, Han T and Rebouças Filho P (2020). An effective approach for CT lung segmentation using mask region-based convolutional neural networks, Artificial Intelligence in Medicine, 103:C, Online publication date: 1-Mar-2020.
- Zhao P, Cai L and Zhou Z (2019). Handling concept drift via model reuse, Machine Language, 109:3, (533-568), Online publication date: 1-Mar-2020.
- Liu W, Chen J, Wang Y, Gao P, Lei Z, Ma X and Zhang X (2020). Quantum-Based Feature Selection for Multiclassification Problem in Complex Systems with Edge Computing, Complexity, 2020, Online publication date: 1-Jan-2020.
- Li X, Chang D, Ma Z, Tan Z, Xue J, Cao J, Yu J and Guo J (2020). OSLNet: Deep Small-Sample Classification With an Orthogonal Softmax Layer, IEEE Transactions on Image Processing, 29, (6482-6495), Online publication date: 1-Jan-2020.
- Pagani S, Manoj P, Jantsch A and Henkel J (2019). Machine Learning for Power, Energy, and Thermal Management on Multicore Processors: A Survey, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39:1, (101-116), Online publication date: 1-Jan-2020.
- Alqahtani F and Alsulaiman F (2022). Is image-based CAPTCHA secure against attacks based on machine learning? An experimental study, Computers and Security, 88:C, Online publication date: 1-Jan-2020.
- Connamacher H, Pancha N, Liu R and Ray S (2019). Rankboost: an improvement to Rankboost, Machine Language, 109:1, (51-78), Online publication date: 1-Jan-2020.
- Tu Z, Zhang J and Tao D Theoretical analysis of adversarial learning Proceedings of the 33rd International Conference on Neural Information Processing Systems, (12280-12290)
- Crane R and Roosta F DINGO Proceedings of the 33rd International Conference on Neural Information Processing Systems, (9498-9508)
- Gourdeau P, Kanade V, Kwiatkowska M and Worrell J On the hardness of robust classification Proceedings of the 33rd International Conference on Neural Information Processing Systems, (7446-7455)
- Goldt S, Advani M, Saxe A, Krzakala F and Zdeborová L Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup Proceedings of the 33rd International Conference on Neural Information Processing Systems, (6981-6991)
- Najafi A, Maeda S, Koyama M and Miyato T Robustness to adversarial perturbations in learning from incomplete data Proceedings of the 33rd International Conference on Neural Information Processing Systems, (5541-5551)
- Cortes C, Mohri M and Storcheus D Regularized gradient boosting Proceedings of the 33rd International Conference on Neural Information Processing Systems, (5449-5458)
- Xu L, Niu G, Honda J and Sugiyama M Uncoupled regression from pairwise comparison data Proceedings of the 33rd International Conference on Neural Information Processing Systems, (3992-4002)
- Kallus N and Zhou A The fairness of risk scores beyond classification Proceedings of the 33rd International Conference on Neural Information Processing Systems, (3438-3448)
- Ni C, Charoenphakdee N, Honda J and Sugiyama M On the calibration of multiclass classification with rejection Proceedings of the 33rd International Conference on Neural Information Processing Systems, (2586-2596)
- Hanneke S and Kontorovich A (2022). Optimality of SVM, Theoretical Computer Science, 796:C, (99-113), Online publication date: 3-Dec-2019.
- Adigun O and Kosko B (2020). Noise-boosted bidirectional backpropagation and adversarial learning, Neural Networks, 120:C, (9-31), Online publication date: 1-Dec-2019.
- Wang Z, Wang B, Cheng Y, Li D and Zhang J (2019). Cost-sensitive Fuzzy Multiple Kernel Learning for imbalanced problem, Neurocomputing, 366:C, (178-193), Online publication date: 13-Nov-2019.
- Li M, Gao S, Liang Y, Marks J, Kang Y and Li M A Data-Driven Approach to Understanding and Predicting the Spatiotemporal Availability of Street Parking Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, (536-539)
- Ohno H (2019). Neural network-based transductive regression model, Applied Soft Computing, 84:C, Online publication date: 1-Nov-2019.
- Lacoche J, Duval T, Arnaldi B, Maisel E and Royan J Machine Learning Based Interaction Technique Selection for 3D User Interfaces Virtual Reality and Augmented Reality, (33-51)
- Jia K, Lin J, Tan M and Tao D (2019). Deep Multi-View Learning Using Neuron-Wise Correlation-Maximizing Regularizers, IEEE Transactions on Image Processing, 28:10, (5121-5134), Online publication date: 1-Oct-2019.
- Li Z, Han Z, Xing J, Ye Q, Yu X and Jiao J (2019). High performance person re-identification via a boosting ranking ensemble, Pattern Recognition, 94:C, (187-195), Online publication date: 1-Oct-2019.
- Ashouri A, Killian W, Cavazos J, Palermo G and Silvano C (2018). A Survey on Compiler Autotuning using Machine Learning, ACM Computing Surveys, 51:5, (1-42), Online publication date: 30-Sep-2019.
- Yang P, Xiao Y, Xiao M, Guan Y, Li S and Xiang W (2019). Adaptive Spatial Modulation MIMO Based on Machine Learning, IEEE Journal on Selected Areas in Communications, 37:9, (2117-2131), Online publication date: 1-Sep-2019.
- Bayat M, Ghorbanpour M, Zare R, Jaafari A and Thai Pham B (2019). Application of artificial neural networks for predicting tree survival and mortality in the Hyrcanian forest of Iran, Computers and Electronics in Agriculture, 164:C, Online publication date: 1-Sep-2019.
- Chen C, Liu Y, Kumar M, Qin J and Ren Y (2019). Energy consumption modelling using deep learning embedded semi-supervised learning, Computers and Industrial Engineering, 135:C, (757-765), Online publication date: 1-Sep-2019.
- Viering T, Krijthe J and Loog M (2019). Nuclear discrepancy for single-shot batch active learning, Machine Language, 108:8-9, (1561-1599), Online publication date: 1-Sep-2019.
- Wang J and Geng X Classification with label distribution learning Proceedings of the 28th International Joint Conference on Artificial Intelligence, (3712-3718)
- Chen H, Mo Z, Yang Z and Wang X Theoretical investigation of generalization bound for residual networks Proceedings of the 28th International Joint Conference on Artificial Intelligence, (2081-2087)
- Turki T and Taguchi Y (2022). Machine learning algorithms for predicting drugs–tissues relationships, Expert Systems with Applications: An International Journal, 127:C, (167-186), Online publication date: 1-Aug-2019.
- Tran B, Karimzadehgan M, Pasumarthi R, Bendersky M and Metzler D Domain Adaptation for Enterprise Email Search Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, (25-34)
- Ye Y, Zhang T and Yang C Fisher Loss: A More Discriminative Feature Learning Method in Classification 2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), (746-751)
- Qian C, Tran-Dinh Q, Fu S, Zou C and Liu Y (2019). Robust multicategory support matrix machines, Mathematical Programming: Series A and B, 176:1-2, (429-463), Online publication date: 1-Jul-2019.
- Park Y, Qing J, Shen X and Mozafari B BlinkML Proceedings of the 2019 International Conference on Management of Data, (1135-1152)
- Barceló P, Baumgartner A, Dalmau V and Kimelfeld B Regularizing Conjunctive Features for Classification Proceedings of the 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, (2-16)
- Gonzalez R and Catania C (2019). Time-delayed multiple linear regression for de-noising MEMS inertial sensors, Computers and Electrical Engineering, 76:C, (1-12), Online publication date: 1-Jun-2019.
- Marim M, de Oliveira A and Villela S UFJF-MLTK: a framework for machine learning algorithms Proceedings of the XV Brazilian Symposium on Information Systems, (1-8)
- Rong J, Qin T and An B Competitive Bridge Bidding with Deep Neural Networks Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, (16-24)
- Aldossari S and Chen K (2019). Machine Learning for Wireless Communication Channel Modeling, Wireless Personal Communications: An International Journal, 106:1, (41-70), Online publication date: 1-May-2019.
- Ivanov R, Weimer J, Alur R, Pappas G and Lee I Verisig Proceedings of the 22nd ACM International Conference on Hybrid Systems: Computation and Control, (169-178)
- Turki T and Wang J (2019). Clinical intelligence, Computers in Biology and Medicine, 107:C, (302-322), Online publication date: 1-Apr-2019.
- Lopes R, Santos S and Silva P (2019). Accelerating block coordinate descent methods with identification strategies, Computational Optimization and Applications, 72:3, (609-640), Online publication date: 1-Apr-2019.
- Meena K, Tayal D, Gupta V and Fatima A (2019). Using classification techniques for statistical analysis of Anemia, Artificial Intelligence in Medicine, 94:C, (138-152), Online publication date: 1-Mar-2019.
- Qaadan S, Pendyala A, Schüler M and Glasmachers T Online Budgeted Stochastic Coordinate Ascent for Large-Scale Kernelized Dual Support Vector Machine Training Pattern Recognition Applications and Methods, (23-47)
- Ahmed M (2019). Data summarization, Knowledge and Information Systems, 58:2, (249-273), Online publication date: 1-Feb-2019.
- Varshney L (2019). Mathematical limit theorems for computational creativity, IBM Journal of Research and Development, 63:1, (2:1-2:12), Online publication date: 1-Jan-2019.
- Ding L, Noborio K and Shibuya K (2020). Frost Forecast using Machine Learning - from association to causality, Procedia Computer Science, 159:C, (1001-1010), Online publication date: 1-Jan-2019.
- Estrada D Value Alignment, Fair Play, and the Rights of Service Robots Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, (102-107)
- Zhao H, Zhang S, Wu G, Costeira J, Moura J and Gordon G Adversarial multiple source domain adaptation Proceedings of the 32nd International Conference on Neural Information Processing Systems, (8568-8579)
- Yamane I, Yger F, Atif J and Sugiyama M Uplift modeling from separate labels Proceedings of the 32nd International Conference on Neural Information Processing Systems, (9949-9959)
- Foster D, Sekhari A and Sridharan K Uniform convergence of gradients for non-convex learning and optimization Proceedings of the 32nd International Conference on Neural Information Processing Systems, (8759-8770)
- Ishida T, Niu G and Sugiyama M Binary classification from positive-confidence data Proceedings of the 32nd International Conference on Neural Information Processing Systems, (5921-5932)
- Shahrampour S and Tarokh V Learning bounds for greedy approximation with explicit feature maps from multiple kernels Proceedings of the 32nd International Conference on Neural Information Processing Systems, (4695-4706)
- Li J, Liu Y, Yin R, Zhang H, Ding L and Wang W Multi-class learning Proceedings of the 32nd International Conference on Neural Information Processing Systems, (1593-1602)
- Xu Y and Wang X Understanding weight normalized deep neural networks with rectified linear units Proceedings of the 32nd International Conference on Neural Information Processing Systems, (130-139)
- Le L, Patterson A and White M Supervised autoencoders Proceedings of the 32nd International Conference on Neural Information Processing Systems, (107-117)
- Ngoc M and Park D (2018). Centroid Neural Network with Pairwise Constraints for Semi-supervised Learning, Neural Processing Letters, 48:3, (1721-1747), Online publication date: 1-Dec-2018.
- Tahmasebi B, Maddah-Ali M and Motahari S Information Theory of Mixed Population Genome-Wide Association Studies 2018 IEEE Information Theory Workshop (ITW), (1-5)
- Álvarez Cid-Fuentes J, Szabo C and Falkner K (2018). An adaptive framework for the detection of novel botnets, Computers and Security, 79:C, (148-161), Online publication date: 1-Nov-2018.
- Liu W, Gao P, Yu W, Qu Z and Yang C (2018). Quantum Relief algorithm, Quantum Information Processing, 17:10, (1-15), Online publication date: 1-Oct-2018.
- Glasmachers T and Qaadan S Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search Machine Learning, Optimization, and Data Science, (329-340)
- Yu X, Liu T, Gong M and Tao D Learning with Biased Complementary Labels Computer Vision – ECCV 2018, (69-85)
- Mollajan A, Memarian H and Nabi-Bidhendi M (2018). Fuzzy classifier fusion, Neural Computing and Applications, 30:3, (825-834), Online publication date: 1-Aug-2018.
- Ye H, Sheng X, Zhan D and He P Distance metric facilitated transportation between heterogeneous domains Proceedings of the 27th International Joint Conference on Artificial Intelligence, (3012-3018)
- Lei Y, Lin S and Tang K Generalization bounds for regularized pairwise learning Proceedings of the 27th International Joint Conference on Artificial Intelligence, (2376-2382)
- Turkington R, Mulvenna M, Bond R, O'Neill S and Armour C The application of user event log data for mental health and wellbeing analysis Proceedings of the 32nd International BCS Human Computer Interaction Conference, (1-14)
- Antsaklis P and Rahnama A (2018). Control and Machine Intelligence for System Autonomy, Journal of Intelligent and Robotic Systems, 91:1, (23-34), Online publication date: 1-Jul-2018.
- Arjmand A, Tzallas A, Tsipouras M, Forlano R, Manousou P, Katertsidis N and Giannakeas N Fat Droplets Identification in Liver Biopsies using Supervised Learning Techniques Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference, (434-440)
- Perales-González C, Carbonero-Ruz M, Becerra-Alonso D and Fernández-Navarro F A Preliminary Study of Diversity in Extreme Learning Machines Ensembles Hybrid Artificial Intelligent Systems, (302-314)
- (2018). Matrix-pattern-oriented classifier with boundary projection discrimination, Knowledge-Based Systems, 149:C, (1-17), Online publication date: 1-Jun-2018.
- Wu S, Tong X, Wang W, Xin G, Wang B and Zhou Q Website Defacements Detection Based on Support Vector Machine Classification Method Proceedings of the 2018 International Conference on Computing and Data Engineering, (62-66)
- Zhang C, Pham M, Fu S and Liu Y (2018). Robust multicategory support vector machines using difference convex algorithm, Mathematical Programming: Series A and B, 169:1, (277-305), Online publication date: 1-May-2018.
- Li X, Ren J, Rambhatla S, Xu Y and Haupt J Robust PCA via Dictionary Based Outlier Pursuit 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), (4699-4703)
- Kahng A New directions for learning-based IC design tools and methodologies Proceedings of the 23rd Asia and South Pacific Design Automation Conference, (405-410)
- Tripathi S and Hemachandra N Scalable linear classifiers based on exponential loss function Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, (190-200)
- Kumar A and Sharma R (2018). Linguistic Lyapunov reinforcement learning control for robotic manipulators, Neurocomputing, 272:C, (84-95), Online publication date: 10-Jan-2018.
- Ji S, Yu C, Fung S, Pan S, Long G and Cong G (2018). Supervised Learning for Suicidal Ideation Detection in Online User Content, Complexity, 2018, Online publication date: 1-Jan-2018.
- Wu X, Hu G and Alonso-Betanzos A (2018). Generalization Bounds for Coregularized Multiple Kernel Learning, Computational Intelligence and Neuroscience, 2018, Online publication date: 1-Jan-2018.
- Yan B, Yin M and Sarkar P Convergence of gradient EM on multi-component mixture of Gaussians Proceedings of the 31st International Conference on Neural Information Processing Systems, (6959-6969)
- Bartlett P, Foster D and Telgarsky M Spectrally-normalized margin bounds for neural networks Proceedings of the 31st International Conference on Neural Information Processing Systems, (6241-6250)
- Ishida T, Niu G, Hu W and Sugiyama M Learning from complementary labels Proceedings of the 31st International Conference on Neural Information Processing Systems, (5644-5654)
- Kiryo R, Niu G, du Plessis M and Sugiyama M Positive-unlabeled learning with non-negative risk estimator Proceedings of the 31st International Conference on Neural Information Processing Systems, (1674-1684)
- Bharath B, Nagananda K, Guenduez D and Poor H Learning-Based Content Caching with Time-Varying Popularity Profiles GLOBECOM 2017 - 2017 IEEE Global Communications Conference, (1-6)
- David R, Goldenberg E and Krauthgamer R (2017). Local reconstruction of low-rank matrices and subspaces, Random Structures & Algorithms, 51:4, (607-630), Online publication date: 1-Dec-2017.
- Valadarsky A, Schapira M, Shahaf D and Tamar A Learning to Route Proceedings of the 16th ACM Workshop on Hot Topics in Networks, (185-191)
- Morente-Molinera J, Mezei J, Carlsson C and Herrera-Viedma E (2017). Improving Supervised Learning Classification Methods Using Multigranular Linguistic Modeling and Fuzzy Entropy, IEEE Transactions on Fuzzy Systems, 25:5, (1078-1089), Online publication date: 1-Oct-2017.
- Matsui K, Kumagai W and Kanamori T (2017). Parallel distributed block coordinate descent methods based on pairwise comparison oracle, Journal of Global Optimization, 69:1, (1-21), Online publication date: 1-Sep-2017.
- Xu Y, Xu C, Xu C and Tao D Multi-positive and unlabeled learning Proceedings of the 26th International Joint Conference on Artificial Intelligence, (3182-3188)
- Liu T, Yang Q and Tao D Understanding how feature structure transfers in transfer learning Proceedings of the 26th International Joint Conference on Artificial Intelligence, (2365-2371)
- Fish B and Reyzin L On the complexity of learning from label proportions Proceedings of the 26th International Joint Conference on Artificial Intelligence, (1675-1681)
- Zhang T and Zhou Z Multi-class optimal margin distribution machine Proceedings of the 34th International Conference on Machine Learning - Volume 70, (4063-4071)
- Sakai T, du Plessis M, Niu G and Sugiyama M Semi-supervised classification based on classification from positive and unlabeled data Proceedings of the 34th International Conference on Machine Learning - Volume 70, (2998-3006)
- McNamara D and Balcan M Risk bounds for transferring representations with and without fine-tuning Proceedings of the 34th International Conference on Machine Learning - Volume 70, (2373-2381)
- Dembczyñski K, Kotłowski W, Koyejo O and Natarajan N Consistency analysis for binary classification revisited Proceedings of the 34th International Conference on Machine Learning - Volume 70, (961-969)
- Gottlieb L, Kontorovich A and Krauthgamer R (2017). Efficient Regression in Metric Spaces via Approximate Lipschitz Extension, IEEE Transactions on Information Theory, 63:8, (4838-4849), Online publication date: 1-Aug-2017.
- Morente-Molinera J, Mezei J, Carlsson C and Herrera-Viedma E Using multi-granular fuzzy linguistic modelling methods for supervised classification learning purposes 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), (1-6)
- Karanasiou A and Pinotsis D Towards a legal definition of machine intelligence Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law, (119-128)
- Gay G, Rayadurgam S and Heimdahl M (2017). Automated Steering of Model-Based Test Oracles to Admit Real Program Behaviors, IEEE Transactions on Software Engineering, 43:6, (531-555), Online publication date: 1-Jun-2017.
- Amaral J, Lopes A, Veiga J, Faria A and Melo P (2017). High-accuracy detection of airway obstruction in asthma using machine learning algorithms and forced oscillation measurements, Computer Methods and Programs in Biomedicine, 144:C, (113-125), Online publication date: 1-Jun-2017.
- Tizpaz-Niari S, Černý P, Chang B, Sankaranarayanan S and Trivedi A Discriminating Traces with Time Proceedings, Part II, of the 23rd International Conference on Tools and Algorithms for the Construction and Analysis of Systems - Volume 10206, (21-37)
- Zhang J, Chow C and Xu J (2017). Enabling Kernel-Based Attribute-Aware Matrix Factorization for Rating Prediction, IEEE Transactions on Knowledge and Data Engineering, 29:4, (798-812), Online publication date: 1-Apr-2017.
- Varathan K, Giachanou A and Crestani F (2017). Comparative opinion mining, Journal of the Association for Information Science and Technology, 68:4, (811-829), Online publication date: 1-Apr-2017.
- Xiao Q and Wang Z Ensemble classification based on Random linear base classifiers 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), (2706-2710)
- Phan A, Nguyen M and Bui L (2017). Feature weighting and SVM parameters optimization based on genetic algorithms for classification problems, Applied Intelligence, 46:2, (455-469), Online publication date: 1-Mar-2017.
- Bellaouar S, Cherroun H, Nehar A and Ziadi D Weighted Automata Sequence Kernel Proceedings of the 9th International Conference on Machine Learning and Computing, (48-55)
- Liu T, Tao D, Song M and Maybank S (2017). Algorithm-Dependent Generalization Bounds for Multi-Task Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 39:2, (227-241), Online publication date: 1-Feb-2017.
- Gottlieb L, Kontorovich A and Nisnevitch P (2017). Nearly optimal classification for semimetrics, The Journal of Machine Learning Research, 18:1, (1233-1254), Online publication date: 1-Jan-2017.
- Fraser M Multi-step learning and underlying structure in statistical models Proceedings of the 30th International Conference on Neural Information Processing Systems, (4815-4823)
- Hazan E and Ma T A non-generative framework and convex relaxations for unsupervised learning Proceedings of the 30th International Conference on Neural Information Processing Systems, (3314-3322)
- Cortes C, Kuznetsov V, Mohrii M and Yang S Structured prediction theory based on factor graph complexity Proceedings of the 30th International Conference on Neural Information Processing Systems, (2522-2530)
- Balcan M, Sandholm T and Vitercik E Sample complexity of automated mechanism design Proceedings of the 30th International Conference on Neural Information Processing Systems, (2091-2099)
- Rabusseau G and Kadri H Low-rank regression with tensor responses Proceedings of the 30th International Conference on Neural Information Processing Systems, (1875-1883)
- Cortes C, De Salvo G and Mohri M Boosting with abstention Proceedings of the 30th International Conference on Neural Information Processing Systems, (1668-1676)
- Niu G, du Plessis M, Sakai T, Ma Y and Sugiyama M Theoretical comparisons of positive-unlabeled learning against positive-negative learning Proceedings of the 30th International Conference on Neural Information Processing Systems, (1207-1215)
- Cortes C, DeSalvo G and Mohri M Learning with Rejection Algorithmic Learning Theory, (67-82)
- Toubman A, Roessingh J, van Oijen J, Løvlid R, Ming Hou , Meyer C, Luotsinen L, Rijken R, Harris J and Turčaník M Modeling behavior of Computer Generated Forces with Machine Learning Techniques, the NATO Task Group approach 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), (001906-001911)
- Maximov Y and Reshetova D (2016). Tight risk bounds for multi-class margin classifiers, Pattern Recognition and Image Analysis, 26:4, (673-680), Online publication date: 1-Oct-2016.
- Kim S, Kang S and Kim Y (2016). Anisotropic diffusion noise filtering using region adaptive smoothing strength, Journal of Visual Communication and Image Representation, 40:PA, (384-391), Online publication date: 1-Oct-2016.
- Zadorozhnyi O, Benecke G, Mandt S, Scheffer T and Kloft M Huber-Norm Regularization for Linear Prediction Models European Conference on Machine Learning and Knowledge Discovery in Databases - Volume 9851, (714-730)
- Zhu J, Xu C, Li Z, Fung G, Lin X, Huang J and Huang C (2016). An examination of on-line machine learning approaches for pseudo-random generated data, Cluster Computing, 19:3, (1309-1321), Online publication date: 1-Sep-2016.
- Nazerzadeh H, Paes Leme R, Rostamizadeh A and Syed U Where to Sell Proceedings of the 2016 ACM Conference on Economics and Computation, (597-598)
- Wang B and Pineau J Generalized dictionary for multitask learning with boosting Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, (2097-2103)
- Nezhadbiglari M, Gonçalves M and Almeida J Early Prediction of Scholar Popularity Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries, (181-190)
- Zhang W, Hirzel M and Grove D AQuA Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems, (169-180)
- Swoboda T, Nawroth C, Kaufmann M and Hemmje M Toward Interactive Visualization of Results from Domain-Specific Text Analytics Advanced Visual Interfaces. Supporting Big Data Applications, (75-87)
- Velez G, Quartulli M, Martin A, Otaegui O and Assem H Machine Learning for Autonomic Network Management in a Connected Cars Scenario Proceedings of the 10th International Workshop on Communication Technologies for Vehicles - Volume 9669, (111-120)
- Huang J, Deng Y, Yang Q and Sun J (2016). An Energy-Efficient Train Control Framework for Smart Railway Transportation, IEEE Transactions on Computers, 65:5, (1407-1417), Online publication date: 1-May-2016.
- DeSalvo G and Mohri M Random Composite Forests Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, (1540-1546)
- Alfeld S, Zhu X and Barford P Data poisoning attacks against autoregressive models Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, (1452-1458)
- Tian D, Zhu Y, Xia H, Wang J and Liu H A Quality Analysis Method for the Fuel-level Data of IOV Proceedings of the Second International Conference on Internet of Vehicles - Safe and Intelligent Mobility - Volume 9502, (176-185)
- Kim H and Choi J (2015). Hierarchical multi-class LAD based on OvA-binary tree using genetic algorithm, Expert Systems with Applications: An International Journal, 42:21, (8134-8145), Online publication date: 30-Nov-2015.
- Pasricha S, Ugave V, Anderson C and Han Q LearnLoc Proceedings of the 10th International Conference on Hardware/Software Codesign and System Synthesis, (37-44)
- Desalvo G, Mohri M and Syed U Learning with Deep Cascades Proceedings of the 26th International Conference on Algorithmic Learning Theory - Volume 9355, (254-269)
- Balle B and Mohri M On the Rademacher Complexity of Weighted Automata Proceedings of the 26th International Conference on Algorithmic Learning Theory - Volume 9355, (179-193)
- Goswami P, Amini M and Gaussier E Language-independent Query Representation for IR Model Parameter Estimation on Unlabeled Collections Proceedings of the 2015 International Conference on The Theory of Information Retrieval, (121-130)
- Huang Y, Georgiopoulos M and Anagnostopoulos G Hash function learning via codewords Proceedings of the 2015th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I, (659-674)
- Kaban A Improved Bounds on the Dot Product under Random Projection and Random Sign Projection Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (487-496)
- Liu H, Liu T, Wu J, Tao D and Fu Y Spectral Ensemble Clustering Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (715-724)
- Li Y, Tian X, Liu T and Tao D Multi-task model and feature joint learning Proceedings of the 24th International Conference on Artificial Intelligence, (3643-3649)
- El-Roby A and Aboulnaga A ALEX Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, (1839-1853)
- Chiu A, Garvey J and Abdelrahman T Genesis Proceedings of the 12th ACM International Conference on Computing Frontiers, (1-8)
- Szymczyk P and Szymczyk M (2015). Supervised learning Laplace transform artificial neural networks and using it for automatic classification of geological structure, Neurocomputing, 154:C, (70-76), Online publication date: 22-Apr-2015.
- Guizilini V and Ramos F (2015). Online self-supervised learning for dynamic object segmentation, International Journal of Robotics Research, 34:4-5, (559-581), Online publication date: 1-Apr-2015.
- Lin T, Xue H, Wang L, Huang B and Zha H (2015). Supervised learning via Euler's Elastica models, The Journal of Machine Learning Research, 16:1, (3637-3686), Online publication date: 1-Jan-2015.
- Krueger T, Panknin D and Braun M (2015). Fast cross-validation via sequential testing, The Journal of Machine Learning Research, 16:1, (1103-1155), Online publication date: 1-Jan-2015.
- Marzukhi S, Browne W and Zhang M Three-cornered coevolution learning classifier systems for classification tasks Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation, (549-556)
- Riondato M and Kornaropoulos E Fast approximation of betweenness centrality through sampling Proceedings of the 7th ACM international conference on Web search and data mining, (413-422)
- Ackermann L and Volz B model[NL]generation Proceedings of the 2013 ACM workshop on Domain-specific modeling, (45-50)
- Ziyuan Gu , Saberi M, Sarvi M and Zhiyuan Liu Calibration of traffic flow fundamental diagrams for network simulation applications: A two-stage clustering approach 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), (1348-1353)
- Wilson C and Veeravalli V Adaptive sequential optimization with applications to machine learning 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), (2642-2646)
Index Terms
- Foundations of Machine Learning