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All publications by Dale Schuurmans
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Embedding Inference for Structured Multilabel Prediction
Farzaneh Mirzazadeh, Siamak Ravanbakhsh, Nan Ding and Dale Schuurmans
Advances in Neural Information Processing Systems 28, 2015


Adaptive Monte Carlo via Bandit Allocation
James Neufeld, Andras Gyorgy, Csaba Szepesvari and Dale Schuurmans
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Convex Deep Learning via Normalized Kernels
Özlem Aslan, Xinhua Zhang and Dale Schuurmans
Advances in Neural Information Processing Systems 27, 2014


Polar Operators for Structured Sparse Estimation
Xinhua Zhang, Yao-liang Yu and Dale Schuurmans
Advances in Neural Information Processing Systems 26, 2013


Convex Two-Layer Modeling
Özlem Aslan, Hao Cheng, Xinhua Zhang and Dale Schuurmans
Advances in Neural Information Processing Systems 26, 2013


Characterizing the Representer Theorem
Yaoliang Yu, Hao Cheng, Dale Schuurmans and Csaba Szepesvári
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Accelerated Training for Matrix-norm Regularization: A Boosting Approach
Xinhua Zhang, Dale Schuurmans and Yao-liang Yu
Advances in Neural Information Processing Systems 25, 2012


A Polynomial-time Form of Robust Regression
Ozlem Aslan, Dale Schuurmans and Yao-liang Yu
Advances in Neural Information Processing Systems 25, 2012


Convex Multi-view Subspace Learning
Martha White, Xinhua Zhang, Dale Schuurmans and Yao-liang Yu
Advances in Neural Information Processing Systems 25, 2012


Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations
James Neufeld, Ryan Kiros, Xinhua Zhang, Dale Schuurmans and Yao-liang Yu
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Generalized Optimal Reverse Prediction
Martha White and Dale Schuurmans
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Relaxed Clipping: A Global Training Method for Robust Regression and Classification
Min Yang, Linli Xu, Martha White, Dale Schuurmans and Yao-liang Yu
Advances in Neural Information Processing Systems 23, 2010


Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning
Linli Xu, Martha White and Dale Schuurmans
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Convex Relaxation of Mixture Regression with Efficient Algorithms
Novi Quadrianto, John Lim, Dale Schuurmans and Tibério S. Caetano
Advances in Neural Information Processing Systems 22, 2009


A General Projection Property for Distribution Families
Yao-liang Yu, Yuxi Li, Dale Schuurmans and Csaba Szepesvári
Advances in Neural Information Processing Systems 22, 2009


Dual Temporal Difference Learning
Min Yang, Yuxi Li and Dale Schuurmans
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Learning Exercise Policies for American Options
Yuxi Li, Csaba Szepesvári and Dale Schuurmans
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Discriminative Batch Mode Active Learning
Yuhong Guo and Dale Schuurmans
Advances in Neural Information Processing Systems 20, 2007


Stable Dual Dynamic Programming
Tao Wang, Michael Bowling, Dale Schuurmans and Daniel J. Lizotte
Advances in Neural Information Processing Systems 20, 2007


Convex Relaxations of Latent Variable Training
Yuhong Guo and Dale Schuurmans
Advances in Neural Information Processing Systems 20, 2007


Discriminative unsupervised learning of structured predictors
Linli Xu, Dana F. Wilkinson, Finnegan Southey and Dale Schuurmans
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields
Chi-hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans and Russell Greiner
Advances in Neural Information Processing Systems 19, 2006


implicit Online Learning with Kernels
Li Cheng, Dale Schuurmans, Shaojun Wang, Terry Caelli and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 19, 2006


Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans and Li Cheng
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Bayesian sparse sampling for on-line reward optimization
Tao Wang, Daniel J. Lizotte, Michael H. Bowling and Dale Schuurmans
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Variational Bayesian image modelling
Li Cheng, Feng Jiao, Dale Schuurmans and Shaojun Wang
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Solving cluster ensemble problems by bipartite graph partitioning
Xiaoli Z. Fern, Russ Greiner and Dale Schuurmans
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


Maximum Margin Clustering
Linli Xu, James Neufeld, Bryce Larson and Dale Schuurmans
Advances in Neural Information Processing Systems 17, 2004


Learning Mixture Models with the Latent Maximum Entropy Principle
Shaojun Wang, Dale Schuurmans, Fuchun Peng and Yunxin Zhao
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003


Regularized Greedy Importance Sampling
Finnegan Southey, Dale Schuurmans and Ali Ghodsi
Advances in Neural Information Processing Systems 15, 2002