Dale Schuurmans - Publications

Affiliations: 
University of Waterloo, Waterloo, ON, Canada 
Area:
Computer Science

62 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2015 Elgendi M, Kumar S, Guo L, Rutledge J, Coe JY, Zemp R, Schuurmans D, Adatia I. Detection of Heart Sounds in Children with and without Pulmonary Arterial Hypertension-Daubechies Wavelets Approach. Plos One. 10: e0143146. PMID 26629704 DOI: 10.1371/journal.pone.0143146  1
2014 Aslan Ö, Zhang X, Schuurmans D. Convex deep learning via normalized kernels Advances in Neural Information Processing Systems. 4: 3275-3283.  1
2013 Wang S, Cheng L, Greiner R, Schuurmans D. Exploiting syntactic, semantic, and lexical regularities in language modeling via directed markov random fields Computational Intelligence. 29: 649-679. DOI: 10.1111/j.1467-8640.2012.00436.x  0.48
2012 Wang S, Schuurmans D, Zhao Y. The latent maximum entropy principle Acm Transactions On Knowledge Discovery From Data. 6. DOI: 10.1145/2297456.2297460  0.48
2012 White M, Schuurmans D. Generalized optimal reverse prediction Journal of Machine Learning Research. 22: 1305-1313.  1
2009 Koller D, Schuurmans D, Bengio Y, Bottou L. Preface Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference 1
2008 Guo Y, Schuurmans D. Efficient global optimization for exponential family PCA and low-rank matrix factorization 46th Annual Allerton Conference On Communication, Control, and Computing. 1100-1107. DOI: 10.1109/ALLERTON.2008.4797683  1
2008 Li Y, Schuurmans D. Policy iteration for learning an exercise policy for American options Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5323: 165-178. DOI: 10.1007/978-3-540-89722-4_13  1
2007 Wang T, Bowlingm M, Schuurmans D. Dual representations for dynamic programming and reinforcement learning Proceedings of the 2007 Ieee Symposium On Approximate Dynamic Programming and Reinforcement Learning, Adprl 2007. 44-51. DOI: 10.1109/ADPRL.2007.368168  1
2007 Guo Y, Schuurmans D. Learning gene regulatory networks via globally regularized risk minimization Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4751: 83-95.  1
2007 Lee CH, Wang S, Jiao F, Schuurmans D, Greiner R. Learning to model spatial dependency: Semi-supervised discriminative random fields Advances in Neural Information Processing Systems. 793-800.  0.48
2007 Cheng L, Vishwanathan SVN, Schuurmans D, Wang S, Caelli T. Implicit online learning with kernels Advances in Neural Information Processing Systems. 249-256.  0.48
2006 Jiao F, Xu J, Yu L, Schuurmans D. Protein fold recognition using the gradient boost algorithm. Computational Systems Bioinformatics / Life Sciences Society. Computational Systems Bioinformatics Conference. 43-53. PMID 17369624  1
2006 Caetano TS, Caelli T, Schuurmans D, Barone DA. Graphical models and point pattern matching. Ieee Transactions On Pattern Analysis and Machine Intelligence. 28: 1646-63. PMID 16986545 DOI: 10.1109/TPAMI.2006.207  1
2006 Xu L, Wilkinson D, Southey F, Schuurmans D. Discriminative unsupervised learning of structured predictors Acm International Conference Proceeding Series. 148: 1057-1064. DOI: 10.1145/1143844.1143977  1
2006 Li C, Shaojun W, Schuurmans D, Caelli T, Vishwanathan SVN. An online discriminative approach to background subtraction Proceedings - Ieee International Conference On Video and Signal Based Surveillance 2006, Avss 2006. DOI: 10.1109/AVSS.2006.22  1
2006 Boutilier C, Patrascu R, Poupart P, Schuurmans D. Constraint-based optimization and utility elicitation using the minimax decision criterion Artificial Intelligence. 170: 686-713. DOI: 10.1016/j.artint.2006.02.003  1
2006 Huang J, Tingshao Z, Schuurmans D. Web communities identification from random walks Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4213: 187-198.  1
2006 Linli X, Crammer K, Schuurmans D. Robust support vector machine training via convex outlier ablation Proceedings of the National Conference On Artificial Intelligence. 1: 536-542.  1
2006 Huang J, Tingshao Z, Greiner R, Zhou D, Schuurmans D. Information marginalization on subgraphs Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4213: 199-210.  1
2006 Wang S, Cheng L, Greiner R, Schuurmans D. Stochastic analysis of lexical and semantic enhanced structural language model Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4201: 97-111.  1
2006 Jiao F, Wang S, Lee CH, Greiner R, Schuurmans D. Semi-supervised conditional random fields for improved sequence segmentation and labeling Coling/Acl 2006 - 21st International Conference On Computational Linguistics and 44th Annual Meeting of the Association For Computational Linguistics, Proceedings of the Conference. 1: 209-216.  0.48
2006 Tao W, Poupart P, Bowling M, Schuurmans D. Compact, convex upper bound iteration for approximate POMDP planning Proceedings of the National Conference On Artificial Intelligence. 2: 1245-1251.  1
2005 Qin IW, Schuurmans D. Improved estimation for unsupervised part-of-speech tagging Proceedings of 2005 Ieee International Conference On Natural Language Processing and Knowledge Engineering, Ieee Nlp-Ke'05. 2005: 219-224. DOI: 10.1109/NLPKE.2005.1598738  1
2005 Ghodsi A, Huang J, Southey F, Schuurmans D. Tangent-corrected embedding Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 1: 518-525. DOI: 10.1109/CVPR.2005.339  1
2005 Wang S, Schuurmans D, Peng F, Zhao Y. Combining statistical language models via the latent maximum entropy principle Machine Learning. 60: 229-250. DOI: 10.1007/s10994-005-0928-7  1
2005 Xu L, Schuurmans D. Unsupervised and semi-supervised multi-class support vector machines Proceedings of the National Conference On Artificial Intelligence. 2: 904-910.  1
2005 Xu L, Neufeld J, Larson B, Schuurmans D. Maximum margin clustering Advances in Neural Information Processing Systems 1
2005 Wang T, Lizotte D, Bowling M, Schuurmans D. Bayesian sparse sampling for on-line reward optimization Icml 2005 - Proceedings of the 22nd International Conference On Machine Learning. 961-968.  1
2005 Cheng L, Jiao F, Schuurmans D, Wang S. Variational Bayesian image modelling Icml 2005 - Proceedings of the 22nd International Conference On Machine Learning. 129-136.  1
2004 Wang S, Schuurmans D, Peng F, Zhao Y. Learning mixture models with the regularized latent maximum entropy principle. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 15: 903-16. PMID 15461082 DOI: 10.1109/TNN.2004.828755  1
2004 Huang X, Peng F, An A, Schuurmans D. Dynamic Web log session identification with statistical language models Journal of the American Society For Information Science and Technology. 55: 1290-1303. DOI: 10.1002/asi.20084  1
2004 Greiner R, Schuurmans D. Proceeding, Twenty-First International Conference on Machine Learning, ICML 2004: Preface Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004 1
2004 Ghodsi A, Huang J, Schuurmans D. Transformation-invariant embedding for image analysis Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3024: 519-530.  1
2004 Peng F, Schuurmans D, Wang S. Augmenting naive Bayes classifiers with statistical language models Information Retrieval. 7: 317-345.  1
2004 Wang S, Greiner R, Schuurmans D, Cheng L. Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields 2004 International Symposium On Chinese Spoken Language Processing - Proceedings. 305-308.  1
2003 Ghodsi A, Schuurmans D. Automatic basis selection techniques for RBF networks. Neural Networks : the Official Journal of the International Neural Network Society. 16: 809-16. PMID 12850038 DOI: 10.1016/S0893-6080(03)00118-7  1
2003 Lu F, Schuurmans D. Model-based least-squares policy evaluation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2671: 342-352. DOI: 10.1007/3-540-44886-1_26  1
2003 Huang X, Peng F, An A, Schuurmans D, Cercone N. Session boundary detection for association rule learning using n-gram language models Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2671: 237-251. DOI: 10.1007/3-540-44886-1_19  1
2003 Wang S, Schuurmans D. Learning continuous latent variable models with bregman divergences Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 2842: 190-204.  1
2003 Ghodsi A, Schuurmans D. Automatic basis selection for RBF networks using Stein's unbiased risk estimator Proceedings of the International Joint Conference On Neural Networks. 1: 91-95.  1
2003 Wang S, Schuurmans D. Learning latent variable models with Bregman divergences Ieee International Symposium On Information Theory - Proceedings. 220.  1
2003 Peng F, Schuurmans D. Combining naive Bayes and n-gram language models for text classification Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2633: 335-350.  1
2003 Wang S, Schuurmans D, Peng F, Zhao Y. Semantic N-gram language modeling with the latent maximum entropy principle Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 1: 376-379.  1
2003 Southey F, Schuurmans D, Ghodsi A. Regularized greedy importance sampling Advances in Neural Information Processing Systems 1
2003 Jiao F, Li S, Shum HY, Schuurmans D. Face alignment using statistical models and wavelet features Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 1.  1
2003 Wang S, Schuurmans D, Peng F, Zhao Y. Learning Mixture Models with the Latent Maximum Entropy Principle Proceedings, Twentieth International Conference On Machine Learning. 2: 784-791.  1
2003 Boutilier C, Patrascu R, Poupart P, Schuurmans D. Constraint-based optimization with the minimax decision criterion Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2833: 168-182.  1
2003 Huang X, Peng F, Schuurmans D, Cercone N, Robertson SE. Applying machine learning to text segmentation for information retrieval Information Retrieval. 6: 333-362.  1
2002 Schuurmans D, Southey F. Metric-based methods for adaptive model selection and regularization Machine Learning. 48: 51-84. DOI: 10.1023/A:1013947519741  1
2002 Bengio Y, Schuurmans D. Guest introduction: Special issue on new methods for model selection and model combination Machine Learning. 48: 5-7. DOI: 10.1023/A:1013921901994  1
2002 Schuurmans D, Patrascll R. Direct value-approxiillation for factored MDPs Advances in Neural Information Processing Systems 1
2002 Poupart P, Boutilier C, Patrascu R, Schuurmans D. Piecewise linear value function approximation for factored MDPs Proceedings of the National Conference On Artificial Intelligence. 292-299.  1
2002 Elidan G, Ninio M, Friedman N, Schuurmans D. Data perturbation for escaping local maxima in learning Proceedings of the National Conference On Artificial Intelligence. 132-139.  1
2002 Patrascu R, Poupart P, Schuurmans D, Boutilier C, Guestrin C. Greedy linear value-approximation fo radtored Markov decision processes Proceedings of the National Conference On Artificial Intelligence. 285-291.  1
2002 Peng F, Huang X, Schuurmans D, Cercone N, Robertson SE. Using self-supervised word segmentation in Chinese information retrieval Sigir Forum (Acm Special Interest Group On Information Retrieval). 349-350.  1
2001 Grove AJ, Littlestone N, Schuurmans D. General convergence results for linear discriminant updates Machine Learning. 43: 173-210. DOI: 10.1023/A:1010844028087  1
2001 Schuurmans D, Southey F. Local search characteristics of incomplete SAT procedures Artificial Intelligence. 132: 121-150. DOI: 10.1016/S0004-3702(01)00151-5  1
2001 Peng F, Schuurmans D. Self-supervised chinese word segmentation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2189: 238-247. DOI: 10.1007/3-540-44816-0_24  1
2001 Schuurmans D, Southey F, Holte RC. The exponentiated subgradient algorithm for heuristic Boolean programming Ijcai International Joint Conference On Artificial Intelligence. 334-341.  1
2000 Schuurmans D. Greedy importance sampling Advances in Neural Information Processing Systems. 596-602.  1
1995 Schuurmans D. Characterizing rational versus exponential learning curves Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 904: 272-286.  1
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