Schuurmans, Dale

192 publications

TMLR 2026 Beyond Expectations: Learning with Stochastic Dominance Made Practical Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai

AISTATS 2025 Faster WIND: Accelerating Iterative Best-of-$n$ Distillation for LLM Alignment Tong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai

ICLR 2025 Improving Large Language Model Planning with Action Sequence Similarity Xinran Zhao, Hanie Sedghi, Bernd Bohnet, Dale Schuurmans, Azade Nova

ICLR 2025 Learning Continually by Spectral Regularization Alex Lewandowski, Michał Bortkiewicz, Saurabh Kumar, András György, Dale Schuurmans, Mateusz Ostaszewski, Marlos C. Machado

ICLR 2025 Plastic Learning with Deep Fourier Features Alex Lewandowski, Dale Schuurmans, Marlos C. Machado

NeurIPS 2025 REINFORCE Converges to Optimal Policies with Any Learning Rate Samuel McLaughlin Robertson, Thang D. Chu, Bo Dai, Dale Schuurmans, Csaba Szepesvari, Jincheng Mei

ICML 2025 SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-Training Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie, Dale Schuurmans, Quoc V Le, Sergey Levine, Yi Ma

NeurIPS 2025 The World Is Bigger! a Computationally-Embedded Perspective on the Big World Hypothesis Alex Lewandowski, Aditya A. Ramesh, Edan Meyer, Dale Schuurmans, Marlos C. Machado

ICLR 2025 Toward Understanding In-Context vs. In-Weight Learning Bryan Chan, Xinyi Chen, András György, Dale Schuurmans

ICLR 2025 Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai

NeurIPS 2024 Generative Hierarchical Materials Search Sherry Yang, Simon Batzner, Ruiqi Gao, Muratahan Aykol, Alexander Gaunt, Brendan McMorrow, Danilo Rezende, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk

ICLR 2024 Learning Interactive Real-World Simulators Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Leslie Pack Kaelbling, Dale Schuurmans, Pieter Abbeel

ICML 2024 Position: Video as the New Language for Real-World Decision Making Sherry Yang, Jacob C Walker, Jack Parker-Holder, Yilun Du, Jake Bruce, Andre Barreto, Pieter Abbeel, Dale Schuurmans

ICLR 2024 Probabilistic Adaptation of Black-Box Text-to-Video Models Sherry Yang, Yilun Du, Bo Dai, Dale Schuurmans, Joshua B. Tenenbaum, Pieter Abbeel

ICML 2024 Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai

ICLR 2024 Scalable Diffusion for Materials Generation Sherry Yang, KwangHwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk

NeurIPS 2024 Small Steps No More: Global Convergence of Stochastic Gradient Bandits for Arbitrary Learning Rates Jincheng Mei, Bo Dai, Alekh Agarwal, Sharan Vaswani, Anant Raj, Csaba Szepesvári, Dale Schuurmans

ICML 2024 Target Networks and Over-Parameterization Stabilize Off-Policy Bootstrapping with Function Approximation Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A Ramirez, Christopher K Harris, A. Rupam Mahmood, Dale Schuurmans

NeurIPS 2024 UQE: A Query Engine for Unstructured Databases Hanjun Dai, Bethany Yixin Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans

ICLR 2023 Any-Scale Balanced Samplers for Discrete Space Haoran Sun, Bo Dai, Charles Sutton, Dale Schuurmans, Hanjun Dai

NeurIPS 2023 DISCS: A Benchmark for Discrete Sampling Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai

ICMLW 2023 DISCS: A Benchmark for Discrete Sampling Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Sussman Grathwohl, Dale Schuurmans, Hanjun Dai

ICLR 2023 Dichotomy of Control: Separating What You Can Control from What You Cannot Sherry Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

AISTATS 2023 Discrete Langevin Samplers via Wasserstein Gradient Flow Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans

UAI 2023 Energy-Based Predictive Representations for Partially Observed Reinforcement Learning Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai

ICML 2023 Gradient-Free Structured Pruning with Unlabeled Data Azade Nova, Hanjun Dai, Dale Schuurmans

ICLR 2023 Latent Variable Representation for Reinforcement Learning Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai

NeurIPSW 2023 Learning Interactive Real-World Simulators Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Dale Schuurmans, Pieter Abbeel

NeurIPSW 2023 Learning Interactive Real-World Simulators Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Dale Schuurmans, Pieter Abbeel

NeurIPS 2023 Learning Universal Policies via Text-Guided Video Generation Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel

AISTATS 2023 Learning to Optimize with Stochastic Dominance Constraints Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai

ICLR 2023 Least-to-Most Prompting Enables Complex Reasoning in Large Language Models Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V Le, Ed H. Chi

NeurIPS 2023 Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-Off Zichen Zhang, Johannes Kirschner, Junxi Zhang, Francesco Zanini, Alex Ayoub, Masood Dehghan, Dale Schuurmans

NeurIPS 2023 Ordering-Based Conditions for Global Convergence of Policy Gradient Methods Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvari, Dale Schuurmans

TMLR 2023 Reinforcement Teaching Calarina Muslimani, Alex Lewandowski, Dale Schuurmans, Matthew E. Taylor, Jun Luo

ICML 2023 Revisiting Sampling for Combinatorial Optimization Haoran Sun, Katayoon Goshvadi, Azade Nova, Dale Schuurmans, Hanjun Dai

NeurIPSW 2023 Scalable Diffusion for Materials Generation Sherry Yang, KwangHwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk

NeurIPSW 2023 Scalable Diffusion for Materials Generation Sherry Yang, KwangHwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk

ICLR 2023 Score-Based Continuous-Time Discrete Diffusion Models Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai

ICLR 2023 Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou

ICLR 2023 Spectral Decomposition Representation for Reinforcement Learning Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai

ICML 2023 Stochastic Gradient Succeeds for Bandits Jincheng Mei, Zixin Zhong, Bo Dai, Alekh Agarwal, Csaba Szepesvari, Dale Schuurmans

ICLR 2023 TEMPERA: Test-Time Prompt Editing via Reinforcement Learning Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez

ICLR 2023 What Learning Algorithm Is In-Context Learning? Investigations with Linear Models Ekin Akyürek, Dale Schuurmans, Jacob Andreas, Tengyu Ma, Denny Zhou

AISTATS 2022 Offline Policy Selection Under Uncertainty Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans

AISTATS 2022 The Curse of Passive Data Collection in Batch Reinforcement Learning Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvari

ICML 2022 A Parametric Class of Approximate Gradient Updates for Policy Optimization Ramki Gummadi, Saurabh Kumar, Junfeng Wen, Dale Schuurmans

NeurIPS 2022 A Simple Decentralized Cross-Entropy Method Zichen Zhang, Jun Jin, Martin Jagersand, Jun Luo, Dale Schuurmans

NeurIPS 2022 Chain of Thought Imitation with Procedure Cloning Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

NeurIPS 2022 Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou

ICML 2022 Making Linear MDPs Practical via Contrastive Representation Learning Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph Gonzalez, Dale Schuurmans, Bo Dai

ICML 2022 Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization Hanjun Dai, Mengjiao Yang, Yuan Xue, Dale Schuurmans, Bo Dai

ICMLW 2022 Multimodal Masked Autoencoders Learn Transferable Representations Xinyang Geng, Hao Liu, Lisa Lee, Dale Schuurmans, Sergey Levine, Pieter Abbeel

ICLR 2022 Neural Stochastic Dual Dynamic Programming Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai

NeurIPS 2022 On the Global Convergence Rates of Decentralized SoftMax Gradient Play in Markov Potential Games Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li

NeurIPS 2022 Optimal Scaling for Locally Balanced Proposals in Discrete Spaces Haoran Sun, Hanjun Dai, Dale Schuurmans

NeurIPS 2022 The Role of Baselines in Policy Gradient Optimization Jincheng Mei, Wesley Chung, Valentin Thomas, Bo Dai, Csaba Szepesvari, Dale Schuurmans

ICLR 2022 Understanding and Leveraging Overparameterization in Recursive Value Estimation Chenjun Xiao, Bo Dai, Jincheng Mei, Oscar A Ramirez, Ramki Gummadi, Chris Harris, Dale Schuurmans

ICML 2021 Characterizing the Gap Between Actor-Critic and Policy Gradient Junfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans

NeurIPS 2021 Combiner: Full Attention Transformer with Sparse Computation Cost Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai

AAAI 2021 Deep Probabilistic Canonical Correlation Analysis Mahdi Karami, Dale Schuurmans

ICML 2021 EMaQ: Expected-Max Q-Learning Operator for Simple yet Effective Offline and Online RL Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Shane Gu

ICML 2021 LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou

ICML 2021 Leveraging Non-Uniformity in First-Order Non-Convex Optimization Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans

NeurIPSW 2021 Offline Policy Selection Under Uncertainty Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans

ICML 2021 On the Optimality of Batch Policy Optimization Algorithms Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvari, Dale Schuurmans

NeurIPS 2021 Understanding the Effect of Stochasticity in Policy Optimization Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvari, Dale Schuurmans

NeurIPS 2020 A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs Nevena Lazic, Dong Yin, Mehrdad Farajtabar, Nir Levine, Dilan Gorur, Chris Harris, Dale Schuurmans

ICML 2020 An Optimistic Perspective on Offline Reinforcement Learning Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi

ICML 2020 Batch Stationary Distribution Estimation Junfeng Wen, Bo Dai, Lihong Li, Dale Schuurmans

NeurIPS 2020 CoinDICE: Off-Policy Confidence Interval Estimation Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvari, Dale Schuurmans

ICML 2020 ConQUR: Mitigating Delusional Bias in Deep Q-Learning Dijia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier

ICML 2020 Domain Aggregation Networks for Multi-Source Domain Adaptation Junfeng Wen, Russell Greiner, Dale Schuurmans

ICML 2020 Energy-Based Processes for Exchangeable Data Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans

NeurIPS 2020 Escaping the Gravitational Pull of SoftMax Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvari, Dale Schuurmans

ICLR 2020 GenDICE: Generalized Offline Estimation of Stationary Values Ruiyi Zhang, Bo Dai, Lihong Li, Dale Schuurmans

ICML 2020 Go Wide, Then Narrow: Efficient Training of Deep Thin Networks Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc Le, Qiang Liu, Dale Schuurmans

NeurIPS 2020 Learning Discrete Energy-Based Models via Auxiliary-Variable Local Exploration Hanjun Dai, Rishabh Singh, Bo Dai, Charles A. Sutton, Dale Schuurmans

NeurIPS 2020 Off-Policy Evaluation via the Regularized Lagrangian Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, Dale Schuurmans

ICML 2020 On the Global Convergence Rates of SoftMax Policy Gradient Methods Jincheng Mei, Chenjun Xiao, Csaba Szepesvari, Dale Schuurmans

ICML 2020 Scalable Deep Generative Modeling for Sparse Graphs Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans

NeurIPS 2019 A Geometric Perspective on Optimal Representations for Reinforcement Learning Marc Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taiga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle

IJCAI 2019 Advantage Amplification in Slowly Evolving Latent-State Environments Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier

NeurIPS 2019 Exponential Family Estimation via Adversarial Dynamics Embedding Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans

NeurIPS 2019 Invertible Convolutional Flow Mahdi Karami, Dale Schuurmans, Jascha Sohl-Dickstein, Laurent Dinh, Daniel Duckworth

AISTATS 2019 Kernel Exponential Family Estimation via Doubly Dual Embedding Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He

ICML 2019 Learning to Generalize from Sparse and Underspecified Rewards Rishabh Agarwal, Chen Liang, Dale Schuurmans, Mohammad Norouzi

NeurIPS 2019 Maximum Entropy Monte-Carlo Planning Chenjun Xiao, Ruitong Huang, Jincheng Mei, Dale Schuurmans, Martin Müller

IJCAI 2019 On Principled Entropy Exploration in Policy Optimization Jincheng Mei, Chenjun Xiao, Ruitong Huang, Dale Schuurmans, Martin Müller

NeurIPS 2019 Surrogate Objectives for Batch Policy Optimization in One-Step Decision Making Minmin Chen, Ramki Gummadi, Chris Harris, Dale Schuurmans

ICML 2019 The Value Function Polytope in Reinforcement Learning Robert Dadashi, Adrien Ali Taiga, Nicolas Le Roux, Dale Schuurmans, Marc G. Bellemare

ICML 2019 Understanding the Impact of Entropy on Policy Optimization Zafarali Ahmed, Nicolas Le Roux, Mohammad Norouzi, Dale Schuurmans

NeurIPS 2018 Non-Delusional Q-Learning and Value-Iteration Tyler Lu, Dale Schuurmans, Craig Boutilier

IJCAI 2018 Planning and Learning with Stochastic Action Sets Craig Boutilier, Alon Cohen, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans

ICML 2018 Smoothed Action Value Functions for Learning Gaussian Policies Ofir Nachum, Mohammad Norouzi, George Tucker, Dale Schuurmans

ICLR 2018 Trust-PCL: An Off-Policy Trust Region Method for Continuous Control Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans

AISTATS 2018 Variational Rejection Sampling Aditya Grover, Ramki Gummadi, Miguel Lázaro-Gredilla, Dale Schuurmans, Stefano Ermon

NeurIPS 2017 Bridging the Gap Between Value and Policy Based Reinforcement Learning Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans

JMLR 2017 Generalized Conditional Gradient for Sparse Estimation Yaoliang Yu, Xinhua Zhang, Dale Schuurmans

UAI 2017 Holographic Feature Representations of Deep Networks Martin A. Zinkevich, Alex Davies, Dale Schuurmans

ICLR 2017 Improving Policy Gradient by Exploring Under-Appreciated Rewards Ofir Nachum, Mohammad Norouzi, Dale Schuurmans

IJCAI 2017 Logistic Markov Decision Processes Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu

NeurIPS 2017 Multi-View Matrix Factorization for Linear Dynamical System Estimation Mahdi Karami, Martha White, Dale Schuurmans, Csaba Szepesvari

NeurIPS 2016 Deep Learning Games Dale Schuurmans, Martin A Zinkevich

AAAI 2016 Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA Dale Schuurmans, Michael P. Wellman

NeurIPS 2016 Reward Augmented Maximum Likelihood for Neural Structured Prediction Mohammad Norouzi, Samy Bengio, Zhifeng Chen, Navdeep Jaitly, Mike Schuster, Yonghui Wu, Dale Schuurmans

AISTATS 2016 Scalable and Sound Low-Rank Tensor Learning Hao Cheng, Yaoliang Yu, Xinhua Zhang, Eric P. Xing, Dale Schuurmans

AISTATS 2016 Stochastic Neural Networks with Monotonic Activation Functions Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner

IJCAI 2015 Correcting Covariate Shift with the Frank-Wolfe Algorithm Junfeng Wen, Russell Greiner, Dale Schuurmans

NeurIPS 2015 Embedding Inference for Structured Multilabel Prediction Farzaneh Mirzazadeh, Siamak Ravanbakhsh, Nan Ding, Dale Schuurmans

ECML-PKDD 2015 Generalization in Unsupervised Learning Karim T. Abou-Moustafa, Dale Schuurmans

AAAI 2015 Optimal Estimation of Multivariate ARMA Models Martha White, Junfeng Wen, Michael Bowling, Dale Schuurmans

ECML-PKDD 2015 Scalable Metric Learning for Co-Embedding Farzaneh Mirzazadeh, Martha White, András György, Dale Schuurmans

ICCV 2015 Semi-Supervised Zero-Shot Classification with Label Representation Learning Xin Li, Yuhong Guo, Dale Schuurmans

AISTATS 2015 Variance Reduction via Antithetic Markov Chains James Neufeld, Dale Schuurmans, Michael H. Bowling

ICML 2014 Adaptive Monte Carlo via Bandit Allocation James Neufeld, Andras Gyorgy, Csaba Szepesvari, Dale Schuurmans

AAAI 2014 Convex Co-Embedding Farzaneh Mirzazadeh, Yuhong Guo, Dale Schuurmans

NeurIPS 2014 Convex Deep Learning via Normalized Kernels Özlem Aslan, Xinhua Zhang, Dale Schuurmans

ICML 2013 Characterizing the Representer Theorem Yaoliang Yu, Hao Cheng, Dale Schuurmans, Csaba Szepesvari

UAI 2013 Convex Relaxations of Bregman Divergence Clustering Hao Cheng, Xinhua Zhang, Dale Schuurmans

NeurIPS 2013 Convex Two-Layer Modeling Özlem Aslan, Hao Cheng, Xinhua Zhang, Dale Schuurmans

ACML 2013 Learning a Metric Space for Neighbourhood Topology Estimation: Application to Manifold Learning Karim Abou- Moustafa, Dale Schuurmans, Frank Ferrie

ECML-PKDD 2013 Multi-Label Classification with Output Kernels Yuhong Guo, Dale Schuurmans

NeurIPS 2013 Polar Operators for Structured Sparse Estimation Xinhua Zhang, Yao-Liang Yu, Dale Schuurmans

NeurIPS 2012 A Polynomial-Time Form of Robust Regression Yao-liang Yu, Özlem Aslan, Dale Schuurmans

NeurIPS 2012 Accelerated Training for Matrix-Norm Regularization: A Boosting Approach Xinhua Zhang, Dale Schuurmans, Yao-liang Yu

NeurIPS 2012 Convex Multi-View Subspace Learning Martha White, Xinhua Zhang, Dale Schuurmans, Yao-liang Yu

AISTATS 2012 Generalized Optimal Reverse Prediction Martha White, Dale Schuurmans

ICML 2012 Regularizers Versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations James Neufeld, Yaoliang Yu, Xinhua Zhang, Ryan Kiros, Dale Schuurmans

ECML-PKDD 2012 Semi-Supervised Multi-Label Classification - A Simultaneous Large-Margin, Subspace Learning Approach Yuhong Guo, Dale Schuurmans

AAAI 2011 Adaptive Large Margin Training for Multilabel Classification Yuhong Guo, Dale Schuurmans

AAAI 2011 Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions Xinhua Zhang, Yaoliang Yu, Martha White, Ruitong Huang, Dale Schuurmans

IJCAI 2011 Modular Community Detection in Networks Wenye Li, Dale Schuurmans

UAI 2011 Rank/Norm Regularization with Closed-Form Solutions: Application to Subspace Clustering Yaoliang Yu, Dale Schuurmans

NeurIPS 2010 Relaxed Clipping: A Global Training Method for Robust Regression and Classification Min Yang, Linli Xu, Martha White, Dale Schuurmans, Yao-liang Yu

NeurIPS 2009 A General Projection Property for Distribution Families Yao-liang Yu, Yuxi Li, Dale Schuurmans, Csaba Szepesvári

NeurIPS 2009 Convex Relaxation of Mixture Regression with Efficient Algorithms Novi Quadrianto, John Lim, Dale Schuurmans, Tibério S. Caetano

AISTATS 2009 Dual Temporal Difference Learning Min Yang, Yuxi Li, Dale Schuurmans

CVPR 2009 Fast Normalized Cut with Linear Constraints Linli Xu, Wenye Li, Dale Schuurmans

AISTATS 2009 Learning Exercise Policies for American Options Yuxi Li, Csaba Szepesvari, Dale Schuurmans

ICML 2009 Optimal Reverse Prediction: A Unified Perspective on Supervised, Unsupervised and Semi-Supervised Learning Linli Xu, Martha White, Dale Schuurmans

IJCAI 2007 Automatic Gait Optimization with Gaussian Process Regression Daniel J. Lizotte, Tao Wang, Michael H. Bowling, Dale Schuurmans

NeurIPS 2007 Convex Relaxations of Latent Variable Training Yuhong Guo, Dale Schuurmans

NeurIPS 2007 Discriminative Batch Mode Active Learning Yuhong Guo, Dale Schuurmans

IJCAI 2007 Simple Training of Dependency Parsers via Structured Boosting Qin Iris Wang, Dekang Lin, Dale Schuurmans

NeurIPS 2007 Stable Dual Dynamic Programming Tao Wang, Michael Bowling, Dale Schuurmans, Daniel J. Lizotte

AAAI 2006 Compact, Convex Upper Bound Iteration for Approximate POMDP Planning Tao Wang, Pascal Poupart, Michael H. Bowling, Dale Schuurmans

UAI 2006 Convex Structure Learning for Bayesian Networks: Polynomial Feature Selection and Approximate Ordering Yuhong Guo, Dale Schuurmans

ICML 2006 Discriminative Unsupervised Learning of Structured Predictors Linli Xu, Dana F. Wilkinson, Finnegan Southey, Dale Schuurmans

NeurIPS 2006 Implicit Online Learning with Kernels Li Cheng, Dale Schuurmans, Shaojun Wang, Terry Caelli, S.v.n. Vishwanathan

NeurIPS 2006 Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields Chi-hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner

AAAI 2006 Robust Support Vector Machine Training via Convex Outlier Ablation Linli Xu, Koby Crammer, Dale Schuurmans

ICML 2005 Bayesian Sparse Sampling for On-Line Reward Optimization Tao Wang, Daniel J. Lizotte, Michael H. Bowling, Dale Schuurmans

MLJ 2005 Combining Statistical Language Models via the Latent Maximum Entropy Principle Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

ICML 2005 Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random Fields Shaojun Wang, Shaomin Wang, Russell Greiner, Dale Schuurmans, Li Cheng

IJCAI 2005 Learning Coordination Classifiers Yuhong Guo, Russell Greiner, Dale Schuurmans

UAI 2005 Maximum Margin Bayesian Networks Yuhong Guo, Dana F. Wilkinson, Dale Schuurmans

IJCAI 2005 Regret-Based Utility Elicitation in Constraint-Based Decision Problems Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans

CVPR 2005 Tangent-Corrected Embedding Ali Ghodsi, Jiayuan Huang, Finnegan Southey, Dale Schuurmans

AAAI 2005 Unsupervised and Semi-Supervised Multi-Class Support Vector Machines Linli Xu, Dale Schuurmans

ICML 2005 Variational Bayesian Image Modelling Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang

NeurIPS 2004 Maximum Margin Clustering Linli Xu, James Neufeld, Bryce Larson, Dale Schuurmans

ECCV 2004 Transformation-Invariant Embedding for Image Analysis Ali Ghodsi, Jiayuan Huang, Dale Schuurmans

UAI 2003 Boltzmann Machine Learning with the Latent Maximum Entropy Principle Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

CVPR 2003 Face Alignment Using Statistical Models and Wavelet Features Feng Jiao, Stan Z. Li, Heung-Yeung Shum, Dale Schuurmans

AISTATS 2003 Latent Maximum Entropy Approach for Semantic $n$-Gram Language Modeling Shaojun Wang, Dale Schuurmans, Fuchun Peng

ALT 2003 Learning Continuous Latent Variable Models with Bregman Divergences Shaojun Wang, Dale Schuurmans

ICML 2003 Learning Mixture Models with the Latent Maximum Entropy Principle Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

UAI 2003 Monte Carlo Matrix Inversion Policy Evaluation Fletcher Lu, Dale Schuurmans

ICML 2002 Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs Carlos Guestrin, Relu Patrascu, Dale Schuurmans

AAAI 2002 Data Perturbation for Escaping Local Maxima in Learning Gal Elidan, Matan Ninio, Nir Friedman, Dale Schuurmans

AAAI 2002 Greedy Linear Value-Approximation for Factored Markov Decision Processes Relu Patrascu, Pascal Poupart, Dale Schuurmans, Craig Boutilier, Carlos Guestrin

MLJ 2002 Guest Introduction: Special Issue on New Methods for Model Selection and Model Combination Yoshua Bengio, Dale Schuurmans

ICML 2002 Investigating the Maximum Likelihood Alternative to TD(lambda) Fletcher Lu, Relu Patrascu, Dale Schuurmans

MLJ 2002 Metric-Based Methods for Adaptive Model Selection and Regularization Dale Schuurmans, Finnegan Southey

AAAI 2002 Piecewise Linear Value Function Approximation for Factored MDPs Pascal Poupart, Craig Boutilier, Relu Patrascu, Dale Schuurmans

NeurIPS 2002 Regularized Greedy Importance Sampling Finnegan Southey, Dale Schuurmans, Ali Ghodsi

NeurIPS 2001 Direct Value-Approximation for Factored MDPs Dale Schuurmans, Relu Patrascu

MLJ 2001 General Convergence Results for Linear Discriminant Updates Adam J. Grove, Nick Littlestone, Dale Schuurmans

IJCAI 2001 The Exponentiated Subgradient Algorithm for Heuristic Boolean Programming Dale Schuurmans, Finnegan Southey, Robert C. Holte

ICML 2000 An Adaptive Regularization Criterion for Supervised Learning Dale Schuurmans, Finnegan Southey

AAAI 2000 Local Search Characteristics of Incomplete SAT Procedures Dale Schuurmans, Finnegan Southey

UAI 2000 Monte Carlo Inference via Greedy Importance Sampling Dale Schuurmans, Finnegan Southey

AAAI 1999 Efficient Exploration for Optimizing Immediate Reward Dale Schuurmans, Lloyd G. Greenwald

NeurIPS 1999 Greedy Importance Sampling Dale Schuurmans

AAAI 1998 Boosting in the Limit: Maximizing the Margin of Learned Ensembles Adam J. Grove, Dale Schuurmans

AAAI 1997 A New Metric-Based Approach to Model Selection Dale Schuurmans

ICML 1997 Characterizing the Generalization Performance of Model Selection Strategies Dale Schuurmans, Lyle H. Ungar, Dean P. Foster

COLT 1997 General Convergence Results for Linear Discriminant Updates Adam J. Grove, Nick Littlestone, Dale Schuurmans

UAI 1997 Learning Bayesian Nets That Perform Well Russell Greiner, Adam J. Grove, Dale Schuurmans

IJCAI 1995 Practical PAC Learning Dale Schuurmans, Russell Greiner

COLT 1995 Sequential PAC Learning Dale Schuurmans, Russell Greiner