Browse Books

Zhou L, Koehler F, Sutherland D and Srebro N (2024). Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression, ACM / IMS Journal of Data Science, 1:2, (1-51), Online publication date: 30-Jun-2024.

Yamanishi K and Hirai S (2023). Detecting signs of model change with continuous model selection based on descriptive dimensionality, Applied Intelligence, 53:22, (26454-26471), Online publication date: 1-Nov-2023.

De Leone R, Maggioni F and Spinelli A A Multiclass Robust Twin Parametric Margin Support Vector Machine with an Application to Vehicles Emissions Machine Learning, Optimization, and Data Science, (299-310)

Liu Y, Zhao W and Dong D (2023). Gradient‐free algorithms for distributed online convex optimization, Asian Journal of Control, 25:4, (2451-2468), Online publication date: 2-Jul-2023.

Viering T and Loog M (2023). The Shape of Learning Curves: A Review, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45:6, (7799-7819), Online publication date: 1-Jun-2023.

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.

Montasser O, Hanneke S and Srebro N Adversarially robust learning Proceedings of the 36th International Conference on Neural Information Processing Systems, (37458-37470)

Zhou L, Koehler F, Sur P, Sutherland D and Srebro N A non-asymptotic moreau envelope theory for high-dimensional generalized linear models Proceedings of the 36th International Conference on Neural Information Processing Systems, (21286-21299)

Diakonikolas I, Kane D, Manurangsi P and Ren L Cryptographic hardness of learning halfspaces with massart noise Proceedings of the 36th International Conference on Neural Information Processing Systems, (3624-3636)

Ruiz C, Alaíz C and Dorronsoro J Convex Multi-Task Learning with Neural Networks Hybrid Artificial Intelligent Systems, (223-235)

Li B and Lei Y (2022). Hybrid algorithms with active set prediction for solving linear inequalities in a least squares sense, Numerical Algorithms, 90:3, (1327-1356), Online publication date: 1-Jul-2022.

Fatone L, Funaro D and Manzini G (2022). A Decision-Making Machine Learning Approach in Hermite Spectral Approximations of Partial Differential Equations, Journal of Scientific Computing, 92:1, Online publication date: 1-Jul-2022.

Huang X, Liao Z, Liu B, Tao F, Su B and Lin X (2020). A Novel Method for Constructing Classification Models by Combining Different Biomarker Patterns, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19:2, (786-794), Online publication date: 1-Mar-2022.

Wang C, Liu Y, Jiang A and Zhang Q (2022). A Modeling and Optimizing Method for Electricity Current Intensity of Coal Mills, Scientific Programming, 2022, Online publication date: 1-Jan-2022.

Huang W, Liu H, Zhang Y, Mi R, Tong C, Xiao W and Shuai B (2021). Railway dangerous goods transportation system risk identification, Applied Soft Computing, 109:C, Online publication date: 1-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.

Molitor D, Needell D and Ward R (2020). Bias of Homotopic Gradient Descent for the Hinge Loss, Applied Mathematics and Optimization, 84:1, (621-647), Online publication date: 1-Aug-2021.

Segal S, Adi Y, Pinkas B, Baum C, Ganesh C and Keshet J Fairness in the Eyes of the Data: Certifying Machine-Learning Models Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, (926-935)

Bhardwaj R, Duhoon V and Natella R (2021). Hybrid Models for Weather Parameter Forecasting, Complexity, 2021, Online publication date: 1-Jan-2021.

Zhou J, Li C, Arslan C, Hasanipanah M and Bakhshandeh Amnieh H (2019). Performance evaluation of hybrid FFA-ANFIS and GA-ANFIS models to predict particle size distribution of a muck-pile after blasting, Engineering with Computers, 37:1, (265-274), Online publication date: 1-Jan-2021.

Oono K and Suzuki T Optimization and generalization analysis of transduction through gradient boosting and application to multi-scale graph neural networks Proceedings of the 34th International Conference on Neural Information Processing Systems, (18917-18930)

Salehi F, Abbasi E and Hassibi B The performance analysis of generalized margin maximizer (GMM) on separable data Proceedings of the 37th International Conference on Machine Learning, (8417-8426)

Montasser O, Goel S, Diakonikolas I and Srebro N Efficiently learning adversarially robust halfspaces with noise Proceedings of the 37th International Conference on Machine Learning, (7010-7021)

Grønlund A, Kamma L and Larsen K Near-tight margin-based generalization bounds for support vector machines Proceedings of the 37th International Conference on Machine Learning, (3779-3788)

Chen Q, Xue B and Zhang M Improving symbolic regression based on correlation between residuals and variables Proceedings of the 2020 Genetic and Evolutionary Computation Conference, (922-930)

Feldman V Does learning require memorization? a short tale about a long tail Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, (954-959)

Bouziane H and Chouarfia A (2019). Sequence- and structure-based prediction of amyloidogenic regions in proteins, Soft Computing - A Fusion of Foundations, Methodologies and Applications, 24:5, (3285-3308), Online publication date: 1-Mar-2020.

Kim D, Kang S and Cho S (2020). Expected margin–based pattern selection for support vector machines, Expert Systems with Applications: An International Journal, 139:C, Online publication date: 1-Jan-2020.

Sarkar K A Stacked Ensemble Approach to Bengali Sentiment Analysis Intelligent Human Computer Interaction, (102-111)

Foster D, Krishnamurthy A and Luo H Model selection for contextual bandits Proceedings of the 33rd International Conference on Neural Information Processing Systems, (14741-14752)

Yadav C and Bottou L Cold case Proceedings of the 33rd International Conference on Neural Information Processing Systems, (13465-13474)

Diakonikolas I, Gouleakis T and Tzamos C Distribution-independent PAC learning of halfspaces with massart noise Proceedings of the 33rd International Conference on Neural Information Processing Systems, (4749-4760)

Zhu C, Wang P, Miao D and Zhou R Rank-consistency-based multi-view learning with Universum Proceedings of the 1st International Conference on Advanced Information Science and System, (1-6)

Zhu C, Wang Z, Zhou R, Wei L, Zhang X and Ding Y (2019). Semi-supervised one-pass multi-view learning, Neural Computing and Applications, 31:11, (8117-8134), Online publication date: 1-Nov-2019.

Górriz J, Ramirez J and Suckling J (2019). On the computation of distribution-free performance bounds, Pattern Recognition, 93:C, (1-13), Online publication date: 1-Sep-2019.

Birzhandi P and Youn H (2019). CBCH (clustering-based convex hull) for reducing training time of support vector machine, The Journal of Supercomputing, 75:8, (5261-5279), Online publication date: 1-Aug-2019.

Zhu C, Mei C and Zhou R (2019). Weight-based label-unknown multi-view data set generation approach, Information Processing Letters, 146:C, (1-12), Online publication date: 1-Jun-2019.

Yin J and Li Q (2019). A semismooth Newton method for support vector classification and regression, Computational Optimization and Applications, 73:2, (477-508), Online publication date: 1-Jun-2019.

Zhao J, Xu Y and Fujita H (2019). An improved non-parallel Universum support vector machine and its safe sample screening rule, Knowledge-Based Systems, 170:C, (79-88), Online publication date: 15-Apr-2019.

Kalantari B (2019). An algorithmic separating hyperplane theorem and its applications, Discrete Applied Mathematics, 256:C, (59-82), Online publication date: 15-Mar-2019.

Song L, Minku L and Yao X (2019). Software Effort Interval Prediction via Bayesian Inference and Synthetic Bootstrap Resampling, ACM Transactions on Software Engineering and Methodology, 28:1, (1-46), Online publication date: 23-Feb-2019.

Zhang W, Yu L, Yoshida T and Wang Q (2019). Feature weighted confidence to incorporate prior knowledge into support vector machines for classification, Knowledge and Information Systems, 58:2, (371-397), Online publication date: 1-Feb-2019.

Behera S and Misra R SmartPeak Proceedings of the 2018 Artificial Intelligence and Cloud Computing Conference, (157-165)

Ignatyev N (2018). Structure Choice for Relations between Objects in Metric Classification Algorithms, Pattern Recognition and Image Analysis, 28:4, (695-702), Online publication date: 1-Oct-2018.

Chen D, Zhang X, Wang X and Liu Y (2018). Uncertainty learning of rough set-based prediction under a holistic framework, Information Sciences: an International Journal, 463:C, (129-151), Online publication date: 1-Oct-2018.

Baziar S, Shahripour H, Tadayoni M and Nabi-Bidhendi M (2018). Prediction of water saturation in a tight gas sandstone reservoir by using four intelligent methods, Neural Computing and Applications, 30:4, (1171-1185), Online publication date: 1-Aug-2018.

Gu W, Chen W, Ko C, Lee Y and Chen J (2018). Two smooth support vector machines for $$\varepsilon $$ź-insensitive regression, Computational Optimization and Applications, 70:1, (171-199), Online publication date: 1-May-2018.

Wang H, Xiong J, Yao Z, Lin M and Ren J Research Survey on Support Vector Machine Proceedings of the 10th EAI International Conference on Mobile Multimedia Communications, (95-103)

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)

Foster D, Kale S, Mohri M and Sridharan K Parameter-free online learning via model selection Proceedings of the 31st International Conference on Neural Information Processing Systems, (6022-6032)

Zhu C (2017). Double-fold localized multiple matrix learning machine with Universum, Pattern Analysis & Applications, 20:4, (1091-1118), Online publication date: 1-Nov-2017.

Hofmeyr D (2017). Clustering by Minimum Cut Hyperplanes, IEEE Transactions on Pattern Analysis and Machine Intelligence, 39:8, (1547-1560), Online publication date: 1-Aug-2017.

Li D, Zhu Y, Wang Z, Chong C and Gao D (2017). Regularized Matrix-Pattern-Oriented Classification Machine with Universum, Neural Processing Letters, 45:3, (1077-1098), Online publication date: 1-Jun-2017.

Peng J, Rafferty K and Ferguson S (2017). A fast algorithm for sparse support vector machines for mobile computing applications, Neurocomputing, 230:C, (160-172), Online publication date: 22-Mar-2017.

Ahmed R, Temko A, Marnane W, Boylan G and Lightbody G (2017). Exploring temporal information in neonatal seizures using a dynamic time warping based SVM kernel, Computers in Biology and Medicine, 82:C, (100-110), Online publication date: 1-Mar-2017.

Beygelzimer A, Hsu D, Langford J and Zhang C Search improves label for active learning Proceedings of the 30th International Conference on Neural Information Processing Systems, (3350-3358)

Almuhaideb S and Menai M (2016). Impact of preprocessing on medical data classification, Frontiers of Computer Science: Selected Publications from Chinese Universities, 10:6, (1082-1102), Online publication date: 1-Dec-2016.

Peng J, Rafferty K and Ferguson S (2016). Building support vector machines in the context of regularized least squares, Neurocomputing, 211:C, (129-142), Online publication date: 26-Oct-2016.

Oneto L, Anguita D and Ridella S (2016). A local Vapnik-Chervonenkis complexity, Neural Networks, 82:C, (62-75), Online publication date: 1-Oct-2016.

Chen Q, Xue B, Shang L and Zhang M Improving Generalisation of Genetic Programming for Symbolic Regression with Structural Risk Minimisation Proceedings of the Genetic and Evolutionary Computation Conference 2016, (709-716)

Brocardo M, Traore I and Woungang I (2015). Authorship verification of e-mail and tweet messages applied for continuous authentication, Journal of Computer and System Sciences, 81:8, (1429-1440), Online publication date: 1-Dec-2015.

Yang L, Hanneke S and Carbonell J Bounds on the Minimax Rate for Estimating a Prior over a VC Class from Independent Learning Tasks Proceedings of the 26th International Conference on Algorithmic Learning Theory - Volume 9355, (270-284)

Xi-Zhao Wang , Hong-Jie Xing , Yan Li , Qiang Hua , Chun-Ru Dong and Pedrycz W (2015). A Study on Relationship Between Generalization Abilities and Fuzziness of Base Classifiers in Ensemble Learning, IEEE Transactions on Fuzzy Systems, 23:5, (1638-1654), Online publication date: 1-Oct-2015.

Maglogiannis I, Georgakopoulos S, Tasoulis S and Plagianakos V (2015). A software tool for the automatic detection and quantification of fibrotic tissues in microscopy images, Information Sciences: an International Journal, 308:C, (125-139), Online publication date: 1-Jul-2015.

Taşcı E and Uğur A (2015). Shape and Texture Based Novel Features for Automated Juxtapleural Nodule Detection in Lung CTs, Journal of Medical Systems, 39:5, (1-13), Online publication date: 1-May-2015.

Hanneke S and Yang L (2015). Minimax analysis of active learning, The Journal of Machine Learning Research, 16:1, (3487-3602), Online publication date: 1-Jan-2015.

Vapnik V and Izmailov R (2015). Learning using privileged information, The Journal of Machine Learning Research, 16:1, (2023-2049), Online publication date: 1-Jan-2015.

Wiener Y, Hanneke S and El-Yaniv R (2015). A compression technique for analyzing disagreement-based active learning, The Journal of Machine Learning Research, 16:1, (713-745), Online publication date: 1-Jan-2015.

Singh P, Ferranti F, Deschrijver D, Couckuyt I and Dhaene T Classification aided domain reduction for high dimensional optimization Proceedings of the 2014 Winter Simulation Conference, (3928-3939)

Cumani S and Laface P (2014). Large-scale training of pairwise support vector machines for speaker recognition, IEEE/ACM Transactions on Audio, Speech and Language Processing, 22:11, (1590-1600), Online publication date: 1-Nov-2014.

Yu X, Yang J and Xie Z (2014). Training SVMs on a bound vectors set based on Fisher projection, Frontiers of Computer Science: Selected Publications from Chinese Universities, 8:5, (793-806), Online publication date: 1-Oct-2014.

Diem M, Kleber F and Sablatnig R Ruling analysis and classification of torn documents Proceedings of the 2014 ACM symposium on Document engineering, (63-72)

Hanneke S (2014). Theory of Disagreement-Based Active Learning, Foundations and Trends® in Machine Learning, 7:2-3, (131-309), Online publication date: 12-Jun-2014.

Simić D, Svirăević V and Simić S An Approach of Steel Plates Fault Diagnosis in Multiple Classes Decision Making Proceedings of the 9th International Conference on Hybrid Artificial Intelligence Systems - Volume 8480, (86-97)

Lu Y, Zhu Y, Han M, He J and Zhang Y A survey of GPU accelerated SVM Proceedings of the 2014 ACM Southeast Regional Conference, (1-7)

van Oosten J and Schomaker L (2014). Separability versus prototypicality in handwritten word-image retrieval, Pattern Recognition, 47:3, (1031-1038), Online publication date: 1-Mar-2014.

Fernandez-Lozano C, Seoane J, Gestal M, Gaunt T and Campbell C Texture classification using kernel-based techniques Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I, (427-434)

Loog M and Duin R The dipping phenomenon Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition, (310-317)

Huang S, Yu Y and Zhou Z Multi-label hypothesis reuse Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, (525-533)

Jayne C, Lanitis A and Christodoulou C (2012). One-to-many neural network mapping techniques for face image synthesis, Expert Systems with Applications: An International Journal, 39:10, (9778-9787), Online publication date: 1-Aug-2012.

Martínez-Murcia F, Górriz J, Ramírez J, Puntonet C and Salas-González D (2012). Computer Aided Diagnosis tool for Alzheimer's Disease based on Mann-Whitney-Wilcoxon U-Test, Expert Systems with Applications: An International Journal, 39:10, (9676-9685), Online publication date: 1-Aug-2012.

Kim G, Wu C, Lim S and Kim J (2012). Modified matrix splitting method for the support vector machine and its application to the credit classification of companies in Korea, Expert Systems with Applications: An International Journal, 39:10, (8824-8834), Online publication date: 1-Aug-2012.

Yu T, Wei J and Li J PAC learnability of rough hypercuboid classifier Proceedings of the 8th international conference on Intelligent Computing Theories and Applications, (648-655)

Gasmi K, Kharrat A, Messaoud M and Abid M Automated segmentation of brain tumor using optimal texture features and support vector machine classifier Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II, (230-239)

Teng F, Chen Y and Dang X (2012). Multiclass classification with potential function rules, Pattern Recognition, 45:1, (540-551), Online publication date: 1-Jan-2012.

Toraman C and Can F Ensemble pruning for text categorization based on data partitioning Proceedings of the 7th Asia conference on Information Retrieval Technology, (352-361)

Urolagin S, Prema K and Reddy N Generalization capability of artificial neural network incorporated with pruning method Proceedings of the 2011 international conference on Advanced Computing, Networking and Security, (171-178)

Sidaoui B and Sadouni K Efficient binary tree multiclass SVM using genetic algorithms for vowels recognition Proceedings of the 10th WSEAS international conference on Computational Intelligence, Man-Machine Systems and Cybernetics, and proceedings of the 10th WSEAS international conference on Information Security and Privacy, (228-234)

Buhmann J Context sensitive information Proceedings of the Third Mexican conference on Pattern recognition, (12-21)

Pang S, Ban T, Kadobayashi Y and Kasabov N (2011). Personalized mode transductive spanning SVM classification tree, Information Sciences: an International Journal, 181:11, (2071-2085), Online publication date: 1-Jun-2011.

Chaves R, Ramírez J, Górriz J, Salas-Gonzalez D and López M Distance metric learning as feature reduction technique for the Alzheimer's disease diagnosis Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II, (68-76)

Rakhlin A, Sridharan K and Tewari A Online learning Proceedings of the 23rd International Conference on Neural Information Processing Systems - Volume 2, (1984-1992)

Liotta A, Menkovski V, Exarchakos G and Sánchez A (2010). Quality of Experience Models for Multimedia Streaming, International Journal of Mobile Computing and Multimedia Communications, 2:4, (1-20), Online publication date: 1-Oct-2010.

Tzikopoulos S, Georgiou H, Mavroforakis M and Theodoridis S Shape-based tumor retrieval in mammograms using relevance-feedback techniques Proceedings of the 20th international conference on Artificial neural networks: Part I, (251-260)

Banerjee A and Burlina P (2010). Efficient particle filtering via sparse kernel density estimation, IEEE Transactions on Image Processing, 19:9, (2480-2490), Online publication date: 1-Sep-2010.

Alejo R, Sotoca J, Valdovinos R and Toribio P Edited nearest neighbor rule for improving neural networks classifications Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I, (303-310)

Cawley G and Talbot N (2010). On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation, The Journal of Machine Learning Research, 11, (2079-2107), Online publication date: 1-Mar-2010.

Shi J, Yin W, Osher S and Sajda P (2010). A Fast Hybrid Algorithm for Large-Scale l-Regularized Logistic Regression, The Journal of Machine Learning Research, 11, (713-741), Online publication date: 1-Mar-2010.

Guyon I, Saffari A, Dror G and Cawley G (2010). Model Selection: Beyond the Bayesian/Frequentist Divide, The Journal of Machine Learning Research, 11, (61-87), Online publication date: 1-Mar-2010.

Balcan M and Blum A (2010). A discriminative model for semi-supervised learning, Journal of the ACM, 57:3, (1-46), Online publication date: 1-Mar-2010.

Menkovski V, Oredope A, Liotta A and Sánchez A Predicting quality of experience in multimedia streaming Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia, (52-59)

Kang P and Cho S (2009). A hybrid novelty score and its use in keystroke dynamics-based user authentication, Pattern Recognition, 42:11, (3115-3127), Online publication date: 1-Nov-2009.

Tsai G and Tang A Two-view face recognition using bayesian fusion Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics, (157-162)

Xu Z, Dai M and Meng D (2009). Fast and efficient strategies for model selection of Gaussian support vector machine, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 39:5, (1292-1307), Online publication date: 1-Oct-2009.

Klivans A, Long P and Tang A Baum's Algorithm Learns Intersections of Halfspaces with Respect to Log-Concave Distributions Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, (588-600)

Kramer K, Hall L, Goldgof D, Remsen A and Luo T (2009). Fast support vector machines for continuous data, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 39:4, (989-1001), Online publication date: 1-Aug-2009.

Ghaderi J, Xie L and Shen X (2009). Hierarchical cooperation in ad hoc networks, IEEE Transactions on Information Theory, 55:8, (3425-3436), Online publication date: 1-Aug-2009.

Cherkassky V, Cai F and Liang L Predictive learning with sparse heterogeneous data Proceedings of the 2009 international joint conference on Neural Networks, (3155-3162)

Cai F and Cherkassky V SVM+ regression and multi-task learning Proceedings of the 2009 international joint conference on Neural Networks, (503-509)

El-Yaniv R and Pechyony D (2009). Transductive Rademacher complexity and its applications, Journal of Artificial Intelligence Research, 35:1, (193-234), Online publication date: 1-May-2009.

Gilbert R and Trafalis T (2009). Quadratic programming formulations for classificationand regression, Optimization Methods & Software, 24:2, (175-185), Online publication date: 1-Apr-2009.

Casey K, Garrett A, Gay J, Montgomery L and Dozier G (2009). An evolutionary approach for achieving scalability with general regression neural networks, Natural Computing: an international journal, 8:1, (133-148), Online publication date: 1-Mar-2009.

Yu L, Chen H, Wang S and Lai K (2009). Evolving least squares support vector machines for stock market trend mining, IEEE Transactions on Evolutionary Computation, 13:1, (87-102), Online publication date: 1-Feb-2009.

Eryarsoy E, Koehler G and Aytug H (2009). Using domain-specific knowledge in generalization error bounds for support vector machine learning, Decision Support Systems, 46:2, (481-491), Online publication date: 1-Jan-2009.

Ho T Data Complexity Analysis Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, (986-995)

Bandini S, Vanneschi L, Wuensche A and Shehata A (2008). A Neuro-Genetic Framework for Pattern Recognition in Complex Systems, Fundamenta Informaticae, 87:2, (207-226), Online publication date: 15-Nov-2008.

Kang P and Cho S (2008). Locally linear reconstruction for instance-based learning, Pattern Recognition, 41:11, (3507-3518), Online publication date: 1-Nov-2008.

Huang J, Ling C, Zhang H and Matwin S Proper model selection with significance test Proceedings of the 2008th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I, (536-547)

Su C, Ding S, Jia W, Wang X and Xu X Some Progress of Supervised Learning Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence, (661-666)

Cortes C, Mohri M, Pechyony D and Rastogi A Stability of transductive regression algorithms Proceedings of the 25th international conference on Machine learning, (176-183)

Claeskens G, Croux C and Van Kerckhoven J (2008). An Information Criterion for Variable Selection in Support Vector Machines, The Journal of Machine Learning Research, 9, (541-558), Online publication date: 1-Jun-2008.

Liu Q, He Q and Shi Z Extreme support vector machine classifier Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining, (222-233)

Bandini S, Vanneschi L, Wuensche A and Shehata A (2008). A Neuro-Genetic Framework for Pattern Recognition in Complex Systems, Fundamenta Informaticae, 87:2, (207-226), Online publication date: 1-Apr-2008.

Dougherty J, Tabus I and Astola J (2008). Inference of gene regulatory networks based on a universal minimum description length, EURASIP Journal on Bioinformatics and Systems Biology, 2008, (1-11), Online publication date: 1-Jan-2008.

Guermeur Y (2007). VC Theory of Large Margin Multi-Category Classifiers, The Journal of Machine Learning Research, 8, (2551-2594), Online publication date: 1-Dec-2007.

Barshan B, Aytaç T and Yüzbaşıolu Ç (2007). Target differentiation with simple infrared sensors using statistical pattern recognition techniques, Pattern Recognition, 40:10, (2607-2620), Online publication date: 1-Oct-2007.

Leslie L, Chua T and Ramesh J Annotation of paintings with high-level semantic concepts using transductive inference and ontology-based concept disambiguation Proceedings of the 15th ACM international conference on Multimedia, (443-452)

Hao Z, Wen W, Liu Z and Yang X Real-time foreground-background segmentation using adaptive support vector machine algorithm Proceedings of the 17th international conference on Artificial neural networks, (603-610)

Shah M Sample compression bounds for decision trees Proceedings of the 24th international conference on Machine learning, (799-806)

Adankon M and Cheriet M (2007). Optimizing resources in model selection for support vector machine, Pattern Recognition, 40:3, (953-963), Online publication date: 1-Mar-2007.

Avidan S (2007). Ensemble Tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence, 29:2, (261-271), Online publication date: 1-Feb-2007.

Marchenko Y, Chua T and Jain R Ontology-based annotation of paintings using transductive inference framework Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I, (13-23)

Har-Peled S, Roth D and Zimak D Maximum margin coresets for active and noise tolerant learning Proceedings of the 20th international joint conference on Artifical intelligence, (836-841)

Urmanov A Electronic Prognostics for Computer Servers Proceedings of the 2007 Annual Reliability and Maintainability Symposium, (65-70)

Wang J, Neskovic P and Cooper L (2007). Bayes classification based on minimum bounding spheres, Neurocomputing, 70:4-6, (801-808), Online publication date: 1-Jan-2007.

Collobert R, Sinz F, Weston J and Bottou L (2006). Large Scale Transductive SVMs, The Journal of Machine Learning Research, 7, (1687-1712), Online publication date: 1-Dec-2006.

Takeuchi I, Le Q, Sears T and Smola A (2006). Nonparametric Quantile Estimation, The Journal of Machine Learning Research, 7, (1231-1264), Online publication date: 1-Dec-2006.

Scott C and Nowak R (2006). Learning Minimum Volume Sets, The Journal of Machine Learning Research, 7, (665-704), Online publication date: 1-Dec-2006.

Escalera S, Pujol O and Radeva P Decoding of ternary error correcting output codes Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications, (753-763)

Schütze H, Velipasaoglu E and Pedersen J Performance thresholding in practical text classification Proceedings of the 15th ACM international conference on Information and knowledge management, (662-671)

Yelizaveta M, Tat-Seng C and Ramesh J Semi-supervised annotation of brushwork in paintings domain using serial combinations of multiple experts Proceedings of the 14th ACM international conference on Multimedia, (529-538)

Yelizaveta M, Tat-Seng C and Ramesh J Transductive inference using multiple experts for brushwork annotation in paintings domain Proceedings of the 14th ACM international conference on Multimedia, (157-160)

Kuri-Morales Á and Mejía-Guevara I Evolutionary training of SVM for multiple category classification problems with self-adaptive parameters Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence, (329-338)

Kääriäinen M Active learning in the non-realizable case Proceedings of the 17th international conference on Algorithmic Learning Theory, (63-77)

Shen K, Ong C, Li X, Zheng H and Wilder-Smith E Feature selection using SVM probabilistic outputs Proceedings of the 13 international conference on Neural Information Processing - Volume Part I, (782-791)

Hao Z, Wen W, Yang X, Lu J and Zhang G A fast data preprocessing procedure for support vector regression Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning, (48-56)

Ho T Symmetries from uniform space covering in stochastic discrimination Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition, (22-40)

Ramírez J, Yélamos P, Górriz J, Puntonet C and Segura J SVM-Enabled voice activity detection Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II, (676-681)

Li L and Wan C Support vector machines with beta-mixing input sequences Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I, (928-935)

Yang Z, Zhu W and Ji L SLIT Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I, (895-902)

Yélamos P, Ramírez J, Górriz J, Puntonet C and Segura J Speech event detection using support vector machines Proceedings of the 6th international conference on Computational Science - Volume Part I, (356-363)

Qin Y and Obradovic Z Efficient Learning from Massive Spatial-Temporal Data through Selective Support Vector Propagation Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy, (526-530)

Dai Y and Fletcher R (2006). New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds, Mathematical Programming: Series A and B, 106:3, (403-421), Online publication date: 1-May-2006.

Cherkassky V, Krasnopolsky V, Solomatine D and Valdes J (2006). 2006 Special issue, Neural Networks, 19:2, (113-121), Online publication date: 1-Mar-2006.

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