Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.
Cited By
- Park J, Kim T, Gu C, Kang Y and Cheong J (2024). Dynamic collision estimator for collaborative robots, Robotics and Computer-Integrated Manufacturing, 86:C, Online publication date: 1-Apr-2024.
- López-González C, Gómez-Silva M, Besada-Portas E and Pajares G (2024). Layer factor analysis in convolutional neural networks for explainability, Applied Soft Computing, 150:C, Online publication date: 1-Jan-2024.
- Sun F, Febrianto E, Fernando H, Butler L, Cirak F and Hoult N (2023). Data-informed statistical finite element analysis of rail buckling, Computers and Structures, 289:C, Online publication date: 1-Dec-2023.
- Liu B (2023). Robust sequential online prediction with dynamic ensemble of multiple models, Neurocomputing, 552:C, Online publication date: 1-Oct-2023.
- Izza Y, Huang X, Ignatiev A, Narodytska N, Cooper M and Marques-Silva J (2023). On computing probabilistic abductive explanations, International Journal of Approximate Reasoning, 159:C, Online publication date: 1-Aug-2023.
- Zhang H and Yang L Generalized additive model (GAM) based corrosion growth prediction model using mass in-line inspection (ILI) data Proceedings of the 2023 8th International Conference on Big Data and Computing, (1-9)
- Bucholc M, Titarenko S, Ding X, Canavan C and Chen T (2023). A hybrid machine learning approach for prediction of conversion from mild cognitive impairment to dementia, Expert Systems with Applications: An International Journal, 217:C, Online publication date: 1-May-2023.
- Deja R and Deja G (2024). Fuzzy, Graphical Model of Diabetic Therapy, Procedia Computer Science, 225:C, (1900-1908), Online publication date: 1-Jan-2023.
- Atoui M and Cocquempot V (2023). Explainable root cause and pathway analysis with robust and adaptive statistics, Computers in Industry, 144:C, Online publication date: 1-Jan-2023.
- Zhang B and Shin Y (2022). A Gaussian mixture filter with adaptive refinement for nonlinear state estimation, Signal Processing, 201:C, Online publication date: 1-Dec-2022.
- Akbayrak S, Şenöz İ, Sarı A and de Vries B (2022). Probabilistic programming with stochastic variational message passing, International Journal of Approximate Reasoning, 148:C, (235-252), Online publication date: 1-Sep-2022.
- Wu J, Wang W, Huang L and Zhang F (2022). Intrusion detection technique based on flow aggregation and latent semantic analysis, Applied Soft Computing, 127:C, Online publication date: 1-Sep-2022.
- Balenzuela M, Wills A, Renton C and Ninness B (2022). A new smoothing algorithm for jump Markov linear systems, Automatica (Journal of IFAC), 140:C, Online publication date: 1-Jun-2022.
- Schoeman J, van Daalen C and du Preez J (2022). Degenerate Gaussian factors for probabilistic inference, International Journal of Approximate Reasoning, 143:C, (159-191), Online publication date: 1-Apr-2022.
- Jafadideh A and Asl B (2022). A new data covariance matrix estimation for improving minimum variance brain source localization, Computers in Biology and Medicine, 143:C, Online publication date: 1-Apr-2022.
- Castellana D and Bacciu D (2022). A tensor framework for learning in structured domains, Neurocomputing, 470:C, (405-426), Online publication date: 22-Jan-2022.
- Choi B, Bergés M, Bou-Zeid E and Pozzi M (2021). Short-term probabilistic forecasting of meso-scale near-surface urban temperature fields, Environmental Modelling & Software, 145:C, Online publication date: 1-Nov-2021.
- Harzevili N and Alizadeh S (2022). Analysis and modeling conditional mutual dependency of metrics in software defect prediction using latent variables, Neurocomputing, 460:C, (309-330), Online publication date: 14-Oct-2021.
- Yucesan Y, Dourado A and Viana F (2021). A survey of modeling for prognosis and health management of industrial equipment, Advanced Engineering Informatics, 50:C, Online publication date: 1-Oct-2021.
- Song Y and Qu J (2021). Real-time segmentation of remote sensing images with a combination of clustering and Bayesian approaches, Journal of Real-Time Image Processing, 18:5, (1541-1554), Online publication date: 1-Oct-2021.
- Deng A, Li Y, Lu J and Ramamurthy V On Post-selection Inference in A/B Testing Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, (2743-2752)
- Buschek D, Zürn M and Eiband M The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, (1-13)
- Buschek D and Alt F Building Adaptive Touch Interfaces—Case Study 6 Intelligent Computing for Interactive System Design, (379-406)
- Alizadeh S, Hediehloo A and Harzevili N (2022). Multi independent latent component extension of naive Bayes classifier, Knowledge-Based Systems, 213:C, Online publication date: 15-Feb-2021.
- Antsiperov V Maximum Similarity Method for Image Mining Pattern Recognition. ICPR International Workshops and Challenges, (301-313)
- Brown J, Chambers J, Abate A and Rogers A SMITE Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, (21-30)
- Fränzle M and Kröger P Guess What I’m Doing! Leveraging Applications of Formal Methods, Verification and Validation: Applications, (255-272)
- Doghri T, Szczecinski L, Benesty J and Mitiche A Bilinear Models for Machine Learning Artificial Neural Networks and Machine Learning – ICANN 2020, (687-698)
- Zhou J, Tang Z, Zhao M, Ge X, Zhuang F, Zhou M, Zou L, Yang C and Xiong H Intelligent Exploration for User Interface Modules of Mobile App with Collective Learning Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, (3346-3355)
- Drewitz U, Ihme K, Bahnmüller C, Fleischer T, La H, Pape A, Gräfing D, Niermann D and Trende A Towards User-Focused Vehicle Automation: The Architectural Approach of the AutoAkzept Project HCI in Mobility, Transport, and Automotive Systems. Automated Driving and In-Vehicle Experience Design, (15-30)
- Rojas-Gonzalez S and Van Nieuwenhuyse I (2022). A survey on kriging-based infill algorithms for multiobjective simulation optimization, Computers and Operations Research, 116:C, Online publication date: 1-Apr-2020.
- Hunter A, Polberg S and Thimm M (2020). Epistemic graphs for representing and reasoning with positive and negative influences of arguments, Artificial Intelligence, 281:C, Online publication date: 1-Apr-2020.
- Dabrowski J, Rahman A, Pagendam D and George A (2020). Enforcing mean reversion in state space models for prawn pond water quality forecasting, Computers and Electronics in Agriculture, 168:C, Online publication date: 1-Jan-2020.
- Banerjee A, Gu Q, Sivakumar V and Wu Z Random quadratic forms with dependence Proceedings of the 33rd International Conference on Neural Information Processing Systems, (12599-12609)
- Jacobs B (2019). Learning along a Channel, Electronic Notes in Theoretical Computer Science (ENTCS), 347:C, (143-160), Online publication date: 30-Nov-2019.
- Gomes H, Read J, Bifet A, Barddal J and Gama J (2019). Machine learning for streaming data, ACM SIGKDD Explorations Newsletter, 21:2, (6-22), Online publication date: 26-Nov-2019.
- Wang Y, Willis S, Tsoutsouras V and Stanley-Marbell P (2019). Deriving Equations from Sensor Data Using Dimensional Function Synthesis, ACM Transactions on Embedded Computing Systems, 18:5s, (1-22), Online publication date: 31-Oct-2019.
- Bucholc M, Ding X, Wang H, Glass D, Wang H, Prasad G, Maguire L, Bjourson A, McClean P, Todd S, Finn D and Wong-Lin K (2019). A practical computerized decision support system for predicting the severity of Alzheimer's disease of an individual, Expert Systems with Applications: An International Journal, 130:C, (157-171), Online publication date: 15-Sep-2019.
- Read J, Tziortziotis N and Vazirgiannis M (2019). Error-space representations for multi-dimensional data streams with temporal dependence, Pattern Analysis & Applications, 22:3, (1211-1220), Online publication date: 1-Aug-2019.
- Pop M, Proştean O and Proştean G Multiple Lane Road Car-Following Model using Bayesian Reasoning for Lane Change Behavior Estimation Proceedings of the 3rd International Conference on Future Networks and Distributed Systems, (1-8)
- Lücke J and Forster D (2019). k-means as a variational EM approximation of Gaussian mixture models, Pattern Recognition Letters, 125:C, (349-356), Online publication date: 1-Jul-2019.
- Gyamfi K, Brusey J, Hunt A and Gaura E (2019). A dynamic linear model for heteroscedastic LDA under class imbalance, Neurocomputing, 343:C, (65-75), Online publication date: 28-May-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)
- Wang D, Yang Q, Abdul A and Lim B Designing Theory-Driven User-Centric Explainable AI Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, (1-15)
- Jacobs B (2019). The mathematics of changing one's mind, via Jeffrey's or via Pearl's update rule, Journal of Artificial Intelligence Research, 65:1, (783-806), Online publication date: 1-May-2019.
- Mattos C and Barreto G (2019). A stochastic variational framework for Recurrent Gaussian Processes models, Neural Networks, 112:C, (54-72), Online publication date: 1-Apr-2019.
- KhudaBukhsh W, Kar S, Rizk A and Koeppl H (2019). Provisioning and Performance Evaluation of Parallel Systems with Output Synchronization, ACM Transactions on Modeling and Performance Evaluation of Computing Systems, 4:1, (1-31), Online publication date: 3-Mar-2019.
- Li Y, Zhang K, Wang J and Kumar S Learning adaptive random features Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, (4229-4236)
- Bouhlel M and Martins J (2019). Gradient-enhanced kriging for high-dimensional problems, Engineering with Computers, 35:1, (157-173), Online publication date: 1-Jan-2019.
- Dabrowski J, Rahman A and George A Prediction of Dissolved Oxygen from pH and Water Temperature in Aquaculture Prawn Ponds Proceedings of the Australasian Joint Conference on Artificial Intelligence - Workshops, (2-6)
- Rangapuram S, Seeger M, Gasthaus J, Stella L, Wang Y and Januschowski T Deep state space models for time series forecasting Proceedings of the 32nd International Conference on Neural Information Processing Systems, (7796-7805)
- Zhang L, Huang J, Li X and Xiong L (2018). Vision-Based Parking-Slot Detection, IEEE Transactions on Image Processing, 27:11, (5350-5364), Online publication date: 1-Nov-2018.
- Khorasgani H and Biswas G (2018). A methodology for monitoring smart buildings with incomplete models, Applied Soft Computing, 71:C, (396-406), Online publication date: 1-Oct-2018.
- Kalofolias J, Galbrun E and Miettinen P (2018). From sets of good redescriptions to good sets of redescriptions, Knowledge and Information Systems, 57:1, (21-54), Online publication date: 1-Oct-2018.
- Daraio C, Fabbri F, Gavazzi G, Izzo M, Leuzzi L, Quaglia G and Ruocco G (2018). Assessing the interdependencies between scientific disciplinary profiles, Scientometrics, 116:3, (1785-1803), Online publication date: 1-Sep-2018.
- Ścibior A, Kammar O and Ghahramani Z (2018). Functional programming for modular Bayesian inference, Proceedings of the ACM on Programming Languages, 2:ICFP, (1-29), Online publication date: 30-Jul-2018.
- Dabrowski J, Rahman A, George A, Arnold S and McCulloch J State Space Models for Forecasting Water Quality Variables Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, (177-185)
- Mattsson P, Zachariah D and Stoica P (2022). Recursive nonlinear-system identification using latent variables, Automatica (Journal of IFAC), 93:C, (343-351), Online publication date: 1-Jul-2018.
- Shen Y, Choi A and Darwiche A Conditional PSDDs Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence, (6433-6442)
- Le Caillec J (2018). Testing conditional independence to determine shared information in a data/signal fusion process, Signal Processing, 143:C, (7-19), Online publication date: 1-Feb-2018.
- Gyamfi K, Brusey J, Hunt A and Gaura E (2018). Linear dimensionality reduction for classification via a sequential Bayes error minimisation with an application to flow meter diagnostics, Expert Systems with Applications: An International Journal, 91:C, (252-262), Online publication date: 1-Jan-2018.
- Van Canneyt S, Leroux P, Dhoedt B and Demeester T (2018). Modeling and predicting the popularity of online news based on temporal and content-related features, Multimedia Tools and Applications, 77:1, (1409-1436), Online publication date: 1-Jan-2018.
- Dritsoula L, Loiseau P and Musacchio J (2017). A Game-Theoretic Analysis of Adversarial Classification, IEEE Transactions on Information Forensics and Security, 12:12, (3094-3109), Online publication date: 1-Dec-2017.
- Rodrigues F, Borysov S, Ribeiro B and Pereira F (2017). A Bayesian Additive Model for Understanding Public Transport Usage in Special Events, IEEE Transactions on Pattern Analysis and Machine Intelligence, 39:11, (2113-2126), Online publication date: 1-Nov-2017.
- Pretorius W, Du Preez J and Wolhuter R A 'Socially Aware' CSMA/CA MAC Protocol Proceedings of the ACM Multimedia 2017 Workshop on South African Academic Participation, (7-14)
- Amerini I, Becarelli R, Caldelli R, Melani A and Niccolai M (2017). Smartphone Fingerprinting Combining Features of On-Board Sensors, IEEE Transactions on Information Forensics and Security, 12:10, (2457-2466), Online publication date: 1-Oct-2017.
- Riahi Manesh M, Subramaniam S, Reyes H and Kaabouch N (2017). Real-time spectrum occupancy monitoring using a probabilistic model, Computer Networks: The International Journal of Computer and Telecommunications Networking, 124:C, (87-96), Online publication date: 4-Sep-2017.
- Gyamfi K, Brusey J, Hunt A and Gaura E (2017). Linear classifier design under heteroscedasticity in Linear Discriminant Analysis, Expert Systems with Applications: An International Journal, 79:C, (44-52), Online publication date: 15-Aug-2017.
- Nguyen Q and Hein M The loss surface of deep and wide neural networks Proceedings of the 34th International Conference on Machine Learning - Volume 70, (2603-2612)
- Neller T (2017). AI education, AI Matters, 3:2, (14-15), Online publication date: 13-Jul-2017.
- Wang Y and Chaib-draa B (2017). Bayesian inference for time-varying applications, Neurocomputing, 238:C, (351-364), Online publication date: 17-May-2017.
- Buschek D and Alt F ProbUI Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, (4640-4653)
- Tkachenko M and Lauw H (2017). Comparative Relation Generative Model, IEEE Transactions on Knowledge and Data Engineering, 29:4, (771-783), Online publication date: 1-Apr-2017.
- Read J, Martino L and Hollmén J (2017). Multi-label methods for prediction with sequential data, Pattern Recognition, 63:C, (45-55), Online publication date: 1-Mar-2017.
- Kim K and Cho S (2017). Ensemble bayesian networks evolved with speciation for high-performance prediction in data mining, Soft Computing - A Fusion of Foundations, Methodologies and Applications, 21:4, (1065-1080), Online publication date: 1-Feb-2017.
- Melnyk I and Banerjee A (2017). A spectral algorithm for inference in hidden semi-Markov models, The Journal of Machine Learning Research, 18:1, (1164-1202), Online publication date: 1-Jan-2017.
- Wainer J and Cawley G (2017). Empirical evaluation of resampling procedures for optimising SVM hyperparameters, The Journal of Machine Learning Research, 18:1, (475-509), Online publication date: 1-Jan-2017.
- Kucukelbir A, Tran D, Ranganath R, Gelman A and Blei D (2017). Automatic differentiation variational inference, The Journal of Machine Learning Research, 18:1, (430-474), Online publication date: 1-Jan-2017.
- Zhong H, Xiao J and Risi M (2017). Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm, Scientific Programming, 2017, Online publication date: 1-Jan-2017.
- Wang Y and Chaib-draa B (2017). An online Bayesian filtering framework for Gaussian process regression, Expert Systems with Applications: An International Journal, 67:C, (285-295), Online publication date: 1-Jan-2017.
- Dang S, Chaudhury S, Lall B and Roy P Autoregressive hidden Markov model with missing data for modelling functional MR imaging data Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing, (1-8)
- Wang Y and Chaib-draa B (2016). KNN-based Kalman filter, Knowledge-Based Systems, 114:C, (148-155), Online publication date: 15-Dec-2016.
- Wüthrich M, Trimpe S, Garcia Cifuentes C, Kappler D and Schaal S (2016). A new perspective and extension of the Gaussian Filter, International Journal of Robotics Research, 35:14, (1731-1749), Online publication date: 1-Dec-2016.
- Dabrowski J, Beyers C and de Villiers J (2016). Systemic banking crisis early warning systems using dynamic Bayesian networks, Expert Systems with Applications: An International Journal, 62:C, (225-242), Online publication date: 15-Nov-2016.
- Mutimbu L and Robles-Kelly A (2016). Multiple Illuminant Color Estimation via Statistical Inference on Factor Graphs, IEEE Transactions on Image Processing, 25:11, (5383-5396), Online publication date: 1-Nov-2016.
- Chen Z and Chen C (2016). SCIFNET, Knowledge-Based Systems, 110:C, (30-48), Online publication date: 15-Oct-2016.
- Aldegunde M, Zabaras N and Kristensen J (2016). Quantifying uncertainties in first-principles alloy thermodynamics using cluster expansions, Journal of Computational Physics, 323:C, (17-44), Online publication date: 15-Oct-2016.
- Bernas M and Płaczek B (2016). Period-aware local modelling and data selection for time series prediction, Expert Systems with Applications: An International Journal, 59:C, (60-77), Online publication date: 15-Oct-2016.
- Chaoji V, Rastogi R and Roy G (2016). Machine learning in the real world, Proceedings of the VLDB Endowment, 9:13, (1597-1600), Online publication date: 1-Sep-2016.
- Melnyk I, Banerjee A, Matthews B and Oza N Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (1065-1074)
- Zhang D, Wang J, Yilmaz E, Wang X and Zhou Y Bayesian Performance Comparison of Text Classifiers Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, (15-24)
- Zhou Y, Fenton N and Zhu C (2016). An empirical study of Bayesian network parameter learning with monotonic influence constraints, Decision Support Systems, 87:C, (69-79), Online publication date: 1-Jul-2016.
- Memarzadeh M and Pozzi M (2016). Integrated Inspection Scheduling and Maintenance Planning for Infrastructure Systems, Computer-Aided Civil and Infrastructure Engineering, 31:6, (403-415), Online publication date: 1-Jun-2016.
- Buschek D, De Luca A and Alt F Evaluating the Influence of Targets and Hand Postures on Touch-based Behavioural Biometrics Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, (1349-1361)
- Taraghi B, Saranti A, Legenstein R and Ebner M Bayesian modelling of student misconceptions in the one-digit multiplication with probabilistic programming Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, (449-453)
- Kamper H, Jansen A and Goldwater S (2016). Unsupervised word segmentation and lexicon discovery using acoustic word embeddings, IEEE/ACM Transactions on Audio, Speech and Language Processing, 24:4, (669-679), Online publication date: 1-Apr-2016.
- Castaldo F, Palmieri F and Regazzoni C (2016). Bayesian Analysis of Behaviors and Interactions for Situation Awareness in Transportation Systems, IEEE Transactions on Intelligent Transportation Systems, 17:2, (313-322), Online publication date: 1-Feb-2016.
- Dabrowski J and de Villiers J (2015). A unified model for context-based behavioural modelling and classification, Expert Systems with Applications: An International Journal, 42:19, (6738-6757), Online publication date: 1-Nov-2015.
- Burke M and Lasenby J (2015). Pantomimic Gestures for Human–Robot Interaction, IEEE Transactions on Robotics, 31:5, (1225-1237), Online publication date: 1-Oct-2015.
- Van den Broeck G, Mohan K, Choi A, Darwiche A and Pearl J Efficient algorithms for Bayesian network parameter learning from incomplete data Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, (161-170)
- Teacy W, Julier S, De Nardi R, Rogers A and Jennings N Observation Modelling for Vision-Based Target Search by Unmanned Aerial Vehicles Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, (1607-1614)
- Pejovic V and Musolesi M (2015). Anticipatory Mobile Computing, ACM Computing Surveys, 47:3, (1-29), Online publication date: 16-Apr-2015.
- Helms T, Reinhardt O and Uhrmacher A Bayesian changepoint detection for generic adaptive simulation algorithms Proceedings of the 48th Annual Simulation Symposium, (62-69)
- Vuković N and Miljković Z (2015). Robust sequential learning of feedforward neural networks in the presence of heavy-tailed noise, Neural Networks, 63:C, (31-47), Online publication date: 1-Mar-2015.
- Chiappa S (2014). Explicit-Duration Markov Switching Models, Foundations and Trends® in Machine Learning, 7:6, (803-886), Online publication date: 1-Dec-2014.
- Geetha M, Anandsankar B, Nair L, Amrutha T and Rajeev A An improved Human Action Recognition system using RSD Code generation Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, (1-9)
- Youn S, Gu C and Kim J Probabilistic Bug Localization via Statistical Inference based on Partially Observed Data Proceedings of the 51st Annual Design Automation Conference, (1-6)
- Groh G, Straub F, Eicher J and Grob D Geographic aspects of tie strength and value of information in social networking Proceedings of the 6th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, (1-10)
- Chakrabarti D and Herbrich R Speeding up large-scale learning with a social prior Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, (650-658)
- Bengio Y Deep learning of representations Proceedings of the First international conference on Statistical Language and Speech Processing, (1-37)
- Zhang C and Ré C Towards high-throughput gibbs sampling at scale Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, (397-408)
- Wienß J, Stein M and Ewald R Evaluating simulation software components with player rating systems Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques, (41-50)
- Chen Z (2013). An overview of bayesian methods for neural spike train analysis, Computational Intelligence and Neuroscience, 2013, (1-1), Online publication date: 1-Jan-2013.
- Romero-Ortega L and Robles-Kelly A Colour matching function learning Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition, (318-326)
- Hollmén J Mixture modeling of gait patterns from sensor data Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments, (1-4)
- Furmston T and Barber D Lagrange dual decomposition for finite horizon Markov decision processes Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I, (487-502)
- Furmston T and Barber D Lagrange dual decomposition for finite horizon Markov Decision Processes Proceedings of the 2011th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I, (487-502)
- Furmston T and Barber D Efficient inference in Markov control problems Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence, (221-229)
- Issac J, Wüthrich M, Cifuentes C, Bohg J, Trimpe S and Schaal S Depth-based object tracking using a Robust Gaussian Filter 2016 IEEE International Conference on Robotics and Automation (ICRA), (608-615)
- Luo X, Tong Liu , Shen B, Qinqun , Liwen Gao and Luo X Human indoor localization based on ceiling mounted PIR sensor nodes 2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC), (868-874)
- Bajaj N, Murrell N, Whitney J, Allebach J and Chiu G Expert-prescribed weighting for support vector machine classification 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), (913-918)
- Martinez M and Simari G Explanation-Friendly Query Answering Under Uncertainty Reasoning Web. Explainable Artificial Intelligence, (65-103)
- Bortolussi L and Cairoli F Bayesian Abstraction of Markov Population Models Quantitative Evaluation of Systems, (259-276)
Index Terms
- Bayesian Reasoning and Machine Learning