| 2009 |
|---|
| 81 | | Daphne Koller,
Dale Schuurmans,
Yoshua Bengio,
Léon Bottou:
Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 8-11, 2008
MIT Press 2009 |
| 2008 |
|---|
| 80 | EE | Yuxi Li,
Dale Schuurmans:
Policy Iteration for Learning an Exercise Policy for American Options.
EWRL 2008: 165-178 |
| 2007 |
|---|
| 79 | EE | Qin Iris Wang,
Dekang Lin,
Dale Schuurmans:
Simple Training of Dependency Parsers via Structured Boosting.
IJCAI 2007: 1756-1762 |
| 78 | EE | Daniel J. Lizotte,
Tao Wang,
Michael H. Bowling,
Dale Schuurmans:
Automatic Gait Optimization with Gaussian Process Regression.
IJCAI 2007: 944-949 |
| 77 | EE | Yuhong Guo,
Dale Schuurmans:
Convex Relaxations of Latent Variable Training.
NIPS 2007 |
| 76 | EE | Yuhong Guo,
Dale Schuurmans:
Discriminative Batch Mode Active Learning.
NIPS 2007 |
| 75 | EE | Tao Wang,
Daniel J. Lizotte,
Michael H. Bowling,
Dale Schuurmans:
Stable Dual Dynamic Programming.
NIPS 2007 |
| 74 | EE | Yuhong Guo,
Dale Schuurmans:
Learning Gene Regulatory Networks via Globally Regularized Risk Minimization.
RECOMB-CG 2007: 83-95 |
| 2006 |
|---|
| 73 | | Tao Wang,
Pascal Poupart,
Michael H. Bowling,
Dale Schuurmans:
Compact, Convex Upper Bound Iteration for Approximate POMDP Planning.
AAAI 2006 |
| 72 | | Linli Xu,
Koby Crammer,
Dale Schuurmans:
Robust Support Vector Machine Training via Convex Outlier Ablation.
AAAI 2006 |
| 71 | EE | Feng Jiao,
Shaojun Wang,
Chi-Hoon Lee,
Russell Greiner,
Dale Schuurmans:
Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling.
ACL 2006 |
| 70 | EE | Li Cheng,
Shaojun Wang,
Dale Schuurmans,
Terry Caelli,
S. V. N. Vishwanathan:
An Online Discriminative Approach to Background Subtraction.
AVSS 2006: 2 |
| 69 | EE | Shaojun Wang,
Shaomin Wang,
Li Cheng,
Russell Greiner,
Dale Schuurmans:
Stochastic Analysis of Lexical and Semantic Enhanced Structural Language Model.
ICGI 2006: 97-111 |
| 68 | EE | Linli Xu,
Dana F. Wilkinson,
Finnegan Southey,
Dale Schuurmans:
Discriminative unsupervised learning of structured predictors.
ICML 2006: 1057-1064 |
| 67 | EE | Li Cheng,
S. V. N. Vishwanathan,
Dale Schuurmans,
Shaojun Wang,
Terry Caelli:
implicit Online Learning with Kernels.
NIPS 2006: 249-256 |
| 66 | EE | Chi-Hoon Lee,
Shaojun Wang,
Feng Jiao,
Dale Schuurmans,
Russell Greiner:
Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields.
NIPS 2006: 793-800 |
| 65 | EE | Jiayuan Huang,
Tingshao Zhu,
Dale Schuurmans:
Web Communities Identification from Random Walks.
PKDD 2006: 187-198 |
| 64 | EE | Jiayuan Huang,
Tingshao Zhu,
Russell Greiner,
Dengyong Zhou,
Dale Schuurmans:
Information Marginalization on Subgraphs.
PKDD 2006: 199-210 |
| 63 | EE | Yuhong Guo,
Dale Schuurmans:
Convex Structure Learning for Bayesian Networks: Polynomial Feature Selection and Approximate Ordering.
UAI 2006 |
| 62 | EE | Craig Boutilier,
Relu Patrascu,
Pascal Poupart,
Dale Schuurmans:
Constraint-based optimization and utility elicitation using the minimax decision criterion.
Artif. Intell. 170(8-9): 686-713 (2006) |
| 61 | EE | Tibério S. Caetano,
Terry Caelli,
Dale Schuurmans,
Dante Augusto Couto Barone:
Graphical Models and Point Pattern Matching.
IEEE Trans. Pattern Anal. Mach. Intell. 28(10): 1646-1663 (2006) |
| 2005 |
|---|
| 60 | | Linli Xu,
Dale Schuurmans:
Unsupervised and Semi-Supervised Multi-Class Support Vector Machines.
AAAI 2005: 904-910 |
| 59 | EE | Ali Ghodsi,
Jiayuan Huang,
Finnegan Southey,
Dale Schuurmans:
Tangent-Corrected Embedding.
CVPR (1) 2005: 518-525 |
| 58 | EE | Li Cheng,
Feng Jiao,
Dale Schuurmans,
Shaojun Wang:
Variational Bayesian image modelling.
ICML 2005: 129-136 |
| 57 | EE | Shaojun Wang,
Shaomin Wang,
Russell Greiner,
Dale Schuurmans,
Li Cheng:
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields.
ICML 2005: 948-955 |
| 56 | EE | Tao Wang,
Daniel J. Lizotte,
Michael H. Bowling,
Dale Schuurmans:
Bayesian sparse sampling for on-line reward optimization.
ICML 2005: 956-963 |
| 55 | EE | Yuhong Guo,
Russell Greiner,
Dale Schuurmans:
Learning Coordination Classifiers.
IJCAI 2005: 714-721 |
| 54 | EE | Craig Boutilier,
Relu Patrascu,
Pascal Poupart,
Dale Schuurmans:
Regret-based Utility Elicitation in Constraint-based Decision Problems.
IJCAI 2005: 929-934 |
| 53 | EE | Yuhong Guo,
Dana F. Wilkinson,
Dale Schuurmans:
Maximum Margin Bayesian Networks.
UAI 2005: 233-242 |
| 52 | EE | Shaojun Wang,
Dale Schuurmans,
Fuchun Peng,
Yunxin Zhao:
Combining Statistical Language Models via the Latent Maximum Entropy Principle.
Machine Learning 60(1-3): 229-250 (2005) |
| 2004 |
|---|
| 51 | EE | Ali Ghodsi,
Jiayuan Huang,
Dale Schuurmans:
Transformation-Invariant Embedding for Image Analysis.
ECCV (4) 2004: 519-530 |
| 50 | EE | Linli Xu,
James Neufeld,
Bryce Larson,
Dale Schuurmans:
Maximum Margin Clustering.
NIPS 2004 |
| 49 | | Fuchun Peng,
Dale Schuurmans,
Shaojun Wang:
Augmenting Naive Bayes Classifiers with Statistical Language Models.
Inf. Retr. 7(3-4): 317-345 (2004) |
| 48 | EE | Xiangji Huang,
Fuchun Peng,
Aijun An,
Dale Schuurmans:
Dynamic Web log session identification with statistical language models.
JASIST 55(14): 1290-1303 (2004) |
| 2003 |
|---|
| 47 | EE | Shaojun Wang,
Dale Schuurmans:
Learning Continuous Latent Variable Models with Bregman Divergences.
ALT 2003: 190-204 |
| 46 | EE | Craig Boutilier,
Relu Patrascu,
Pascal Poupart,
Dale Schuurmans:
Constraint-Based Optimization with the Minimax Decision Criterion.
CP 2003: 168-182 |
| 45 | EE | Feng Jiao,
Stan Z. Li,
Heung-Yeung Shum,
Dale Schuurmans:
Face Alignment Using Statistical Models and Wavelet Features.
CVPR (1) 2003: 321-327 |
| 44 | EE | Xiangji Huang,
Fuchun Peng,
Aijun An,
Dale Schuurmans,
Nick Cercone:
Session Boundary Detection for Association Rule Learning Using n-Gram Language Models.
Canadian Conference on AI 2003: 237-251 |
| 43 | EE | Fletcher Lu,
Dale Schuurmans:
Model-Based Least-Squares Policy Evaluation.
Canadian Conference on AI 2003: 342-352 |
| 42 | EE | Fuchun Peng,
Dale Schuurmans,
Vlado Keselj,
Shaojun Wang:
Language Independent Authorship Attribution with Character Level N-Grams.
EACL 2003: 267-274 |
| 41 | EE | Fuchun Peng,
Dale Schuurmans:
Combining Naive Bayes and n-Gram Language Models for Text Classification.
ECIR 2003: 335-350 |
| 40 | EE | Fuchun Peng,
Dale Schuurmans,
Shaojun Wang:
Language and Task Independent Text Categorization with Simple Language Models.
HLT-NAACL 2003 |
| 39 | | Shaojun Wang,
Dale Schuurmans,
Fuchun Peng,
Yunxin Zhao:
Learning Mixture Models with the Latent Maximum Entropy Principle.
ICML 2003: 784-791 |
| 38 | EE | Fuchun Peng,
Xiangji Huang,
Dale Schuurmans,
Shaojun Wang:
Text classification in Asian languages without word segmentation.
IRAL 2003: 41-48 |
| 37 | | Fletcher Lu,
Dale Schuurmans:
Monte Carlo Matrix Inversion Policy Evaluation.
UAI 2003: 386-393 |
| 36 | | Shaojun Wang,
Dale Schuurmans,
Fuchun Peng,
Yunxin Zhao:
Boltzmann Machine Learning with the Latent Maximum Entropy Principle.
UAI 2003: 567-574 |
| 35 | | Xiangji Huang,
Fuchun Peng,
Dale Schuurmans,
Nick Cercone,
Stephen E. Robertson:
Applying Machine Learning to Text Segmentation for Information Retrieval.
Inf. Retr. 6(3-4): 333-362 (2003) |
| 34 | EE | Ali Ghodsi,
Dale Schuurmans:
Automatic basis selection techniques for RBF networks.
Neural Networks 16(5-6): 809-816 (2003) |
| 2002 |
|---|
| 33 | | Relu Patrascu,
Pascal Poupart,
Dale Schuurmans,
Craig Boutilier,
Carlos Guestrin:
Greedy Linear Value-Approximation for Factored Markov Decision Processes.
AAAI/IAAI 2002: 285-291 |
| 32 | | Pascal Poupart,
Craig Boutilier,
Relu Patrascu,
Dale Schuurmans:
Piecewise Linear Value Function Approximation for Factored MDPs.
AAAI/IAAI 2002: 292-299 |
| 31 | EE | Fuchun Peng,
Xiangji Huang,
Dale Schuurmans,
Nick Cercone:
Investigating the Relationship between Word Segmentation Performance and Retrieval Performance in Chinese IR.
COLING 2002 |
| 30 | | Carlos Guestrin,
Relu Patrascu,
Dale Schuurmans:
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs.
ICML 2002: 235-242 |
| 29 | | Fletcher Lu,
Relu Patrascu,
Dale Schuurmans:
Investigating the Maximum Likelihood Alternative to TD(lambda).
ICML 2002: 403-410 |
| 28 | EE | Finnegan Southey,
Dale Schuurmans,
Ali Ghodsi:
Regularized Greedy Importance Sampling.
NIPS 2002: 753-760 |
| 27 | EE | Fuchun Peng,
Xiangji Huang,
Dale Schuurmans,
Nick Cercone,
Stephen E. Robertson:
Using self-supervised word segmentation in Chinese information retrieval.
SIGIR 2002: 349-350 |
| 26 | | Yoshua Bengio,
Dale Schuurmans:
Guest Introduction: Special Issue on New Methods for Model Selection and Model Combination.
Machine Learning 48(1-3): 5-7 (2002) |
| 25 | | Dale Schuurmans,
Finnegan Southey:
Metric-Based Methods for Adaptive Model Selection and Regularization.
Machine Learning 48(1-3): 51-84 (2002) |
| 2001 |
|---|
| 24 | EE | Fuchun Peng,
Dale Schuurmans:
Self-Supervised Chinese Word Segmentation.
IDA 2001: 238-247 |
| 23 | | Dale Schuurmans,
Finnegan Southey,
Robert C. Holte:
The Exponentiated Subgradient Algorithm for Heuristic Boolean Programming.
IJCAI 2001: 334-341 |
| 22 | EE | Dale Schuurmans,
Relu Patrascu:
Direct value-approximation for factored MDPs.
NIPS 2001: 1579-1586 |
| 21 | EE | Fuchun Peng,
Dale Schuurmans:
A Simple Closed-Class/Open-Class Factorization for Improved Language Modeling.
NLPRS 2001: 145-152 |
| 20 | EE | Fuchun Peng,
Dale Schuurmans:
A Hierarchical EM Approach to Word Segmentation.
NLPRS 2001: 475-480 |
| 19 | EE | Dale Schuurmans,
Finnegan Southey:
Local search characteristics of incomplete SAT procedures.
Artif. Intell. 132(2): 121-150 (2001) |
| 18 | | Adam J. Grove,
Nick Littlestone,
Dale Schuurmans:
General Convergence Results for Linear Discriminant Updates.
Machine Learning 43(3): 173-210 (2001) |
| 2000 |
|---|
| 17 | | Dale Schuurmans,
Finnegan Southey:
Local Search Characteristics of Incomplete SAT Procedures.
AAAI/IAAI 2000: 297-302 |
| 16 | | Dale Schuurmans,
Finnegan Southey:
An Adaptive Regularization Criterion for Supervised Learning.
ICML 2000: 847-854 |
| 15 | EE | Dale Schuurmans,
Finnegan Southey:
Monte Carlo inference via greedy importance sampling.
UAI 2000: 523-532 |
| 1999 |
|---|
| 14 | | Dale Schuurmans,
Lloyd Greenwald:
Efficient exploration for optimizing immediate reward.
AAAI/IAAI 1999: 385-392 |
| 13 | EE | Dale Schuurmans:
Greedy Importance Sampling.
NIPS 1999: 596-602 |
| 1998 |
|---|
| 12 | | Adam J. Grove,
Dale Schuurmans:
Boosting in the Limit: Maximizing the Margin of Learned Ensembles.
AAAI/IAAI 1998: 692-699 |
| 1997 |
|---|
| 11 | | Dale Schuurmans:
A New Metric-Based Approach to Model Selection.
AAAI/IAAI 1997: 552-558 |
| 10 | EE | Adam J. Grove,
Nick Littlestone,
Dale Schuurmans:
General Convergence Results for Linear Discriminant Updates.
COLT 1997: 171-183 |
| 9 | | Dale Schuurmans,
Lyle H. Ungar,
Dean P. Foster:
Characterizing the generalization performance of model selection strategies.
ICML 1997: 340-348 |
| 8 | EE | Russell Greiner,
Adam J. Grove,
Dale Schuurmans:
Learning Bayesian Nets that Perform Well.
UAI 1997: 198-207 |
| 7 | | Dale Schuurmans:
Characterizing Rational Versus Exponential learning Curves.
J. Comput. Syst. Sci. 55(1): 140-160 (1997) |
| 1995 |
|---|
| 6 | EE | Dale Schuurmans,
Russell Greiner:
Sequential PAC Learning.
COLT 1995: 377-384 |
| 5 | | Dale Schuurmans:
Characterizing rational versus exponential learning curves.
EuroCOLT 1995: 272-286 |
| 4 | | Dale Schuurmans,
Russell Greiner:
Practical PAC Learning.
IJCAI 1995: 1169-1177 |
| 1992 |
|---|
| 3 | | Russell Greiner,
Dale Schuurmans:
Learning an Optimally Accurate Representation System.
ECAI Workshop on Knowledge Representation and Reasoning 1992: 145-159 |
| 2 | | Russell Greiner,
Dale Schuurmans:
Learning Useful Horn Approximations.
KR 1992: 383-392 |
| 1989 |
|---|
| 1 | | Dale Schuurmans,
Jonathan Schaeffer:
Representational Difficulties with Classifier Systems.
ICGA 1989: 328-333 |
