← Authors

Dale Schuurmans

124 papers · 2002–2025 · 15 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (15) 🐝 Cross-Pollinator (9) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (43) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (23) 🏠 Conference Loyalist (45) 🌟 Keyword Trendsetter Combo (9) πŸ“› The Namer πŸ† Keyword Champion πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ”¬ Deep Specialist (17) 🀝 Dynamic Duo (39) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (204) ❓ The Questioner πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (14) ⚑ Prolific Year (14) πŸ’Ž Century Club (124)

Conferences

NIPS (45) ICML (29) ICLR (21) AISTATS (11) IJCAI (5) ACL (2) COLING (2) CONLL (2) AAAI (1) ACML (1) EACL (1) ICCV (1) JMLR (1) NAACL (1) UAI (1)

Top co-authors

Bo Dai (39) Hanjun Dai (21) Jincheng Mei (16) Csaba SzepesvΓ‘ri (15) Chenjun Xiao (12) Ofir Nachum (9) Yaoliang Yu (9) Sherry Yang (9) Xinhua Zhang (7) Pieter Abbeel (7)

Research topics

Reinforcement Learning (1) Applications (1)

Keywords

convex optimization (10) reinforcement learning (9) neural network (6) representation learning (5) variational inference (5) policy learning (5) stochastic optimization (4) markov chain monte carlo (4) function approximation (4) policy optimization (4) value iteration (4) stationary distribution (4) markov decision process (4) sample efficiency (4) policy gradient (4) value function (4) off-policy evaluation (4) generative model (4) neural network optimization (3) deep learning (3)

Papers

SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training ICML 2025
Plastic Learning with Deep Fourier Features ICLR 2025
Toward Understanding In-context vs. In-weight Learning ICLR 2025
Faster WIND: Accelerating Iterative Best-of-$N$ Distillation for LLM Alignment AISTATS 2025
Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF ICLR 2025
Improving Large Language Model Planning with Action Sequence Similarity ICLR 2025
Learning Continually by Spectral Regularization ICLR 2025
Position: Video as the New Language for Real-World Decision Making ICML 2024
UQE: A Query Engine for Unstructured Databases NIPS 2024
Generative Hierarchical Materials Search NIPS 2024
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates NIPS 2024
Learning Interactive Real-World Simulators ICLR 2024
Scalable Diffusion for Materials Generation ICLR 2024
Probabilistic Adaptation of Black-Box Text-to-Video Models ICLR 2024
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning ICML 2024
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation ICML 2024
Energy-based Predictive Representations for Partially Observed Reinforcement Learning UAI 2023
Any-scale Balanced Samplers for Discrete Space ICLR 2023
Latent Variable Representation for Reinforcement Learning ICLR 2023
Revisiting Sampling for Combinatorial Optimization ICML 2023
TEMPERA: Test-Time Prompt Editing via Reinforcement Learning ICLR 2023
Dichotomy of Control: Separating What You Can Control from What You Cannot ICLR 2023
​​What learning algorithm is in-context learning? Investigations with linear models ICLR 2023
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models ICLR 2023
Self-Consistency Improves Chain of Thought Reasoning in Language Models ICLR 2023
DISCS: A Benchmark for Discrete Sampling NIPS 2023
Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off NIPS 2023
Ordering-based Conditions for Global Convergence of Policy Gradient Methods NIPS 2023
Learning Universal Policies via Text-Guided Video Generation NIPS 2023
Discrete Langevin Samplers via Wasserstein Gradient Flow AISTATS 2023
Learning to Optimize with Stochastic Dominance Constraints AISTATS 2023
Gradient-Free Structured Pruning with Unlabeled Data ICML 2023
Stochastic Gradient Succeeds for Bandits ICML 2023
Spectral Decomposition Representation for Reinforcement Learning ICLR 2023
Score-based Continuous-time Discrete Diffusion Models ICLR 2023
Offline Policy Selection under Uncertainty AISTATS 2022
Neural Stochastic Dual Dynamic Programming ICLR 2022
Understanding and Leveraging Overparameterization in Recursive Value Estimation ICLR 2022
Making Linear MDPs Practical via Contrastive Representation Learning ICML 2022
A Parametric Class of Approximate Gradient Updates for Policy Optimization ICML 2022
On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games NIPS 2022
The Role of Baselines in Policy Gradient Optimization NIPS 2022
Optimal Scaling for Locally Balanced Proposals in Discrete Spaces NIPS 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models NIPS 2022
Chain of Thought Imitation with Procedure Cloning NIPS 2022
A Simple Decentralized Cross-Entropy Method NIPS 2022
Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization ICML 2022
The Curse of Passive Data Collection in Batch Reinforcement Learning AISTATS 2022
Characterizing the Gap Between Actor-Critic and Policy Gradient ICML 2021
LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs ICML 2021
Leveraging Non-uniformity in First-order Non-convex Optimization ICML 2021
Deep Probabilistic Canonical Correlation Analysis AAAI 2021
Combiner: Full Attention Transformer with Sparse Computation Cost NIPS 2021
Understanding the Effect of Stochasticity in Policy Optimization NIPS 2021
EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL ICML 2021
On the Optimality of Batch Policy Optimization Algorithms ICML 2021
GenDICE: Generalized Offline Estimation of Stationary Values ICLR 2020
An Optimistic Perspective on Offline Reinforcement Learning ICML 2020
Off-Policy Evaluation via the Regularized Lagrangian NIPS 2020
CoinDICE: Off-Policy Confidence Interval Estimation NIPS 2020
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration NIPS 2020
A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs NIPS 2020
Escaping the Gravitational Pull of Softmax NIPS 2020
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks ICML 2020
Energy-Based Processes for Exchangeable Data ICML 2020
Domain Aggregation Networks for Multi-Source Domain Adaptation ICML 2020
Batch Stationary Distribution Estimation ICML 2020
ConQUR: Mitigating Delusional Bias in Deep Q-Learning ICML 2020
On the Global Convergence Rates of Softmax Policy Gradient Methods ICML 2020
Scalable Deep Generative Modeling for Sparse Graphs ICML 2020
Understanding the Impact of Entropy on Policy Optimization ICML 2019
The Value Function Polytope in Reinforcement Learning ICML 2019
Kernel Exponential Family Estimation via Doubly Dual Embedding AISTATS 2019
On Principled Entropy Exploration in Policy Optimization IJCAI 2019
Invertible Convolutional Flow NIPS 2019
Surrogate Objectives for Batch Policy Optimization in One-step Decision Making NIPS 2019
Maximum Entropy Monte-Carlo Planning NIPS 2019
Exponential Family Estimation via Adversarial Dynamics Embedding NIPS 2019
A Geometric Perspective on Optimal Representations for Reinforcement Learning NIPS 2019
Advantage Amplification in Slowly Evolving Latent-State Environments IJCAI 2019
Learning to Generalize from Sparse and Underspecified Rewards ICML 2019
Trust-PCL: An Off-Policy Trust Region Method for Continuous Control ICLR 2018
Variational Rejection Sampling AISTATS 2018
Non-delusional Q-learning and value-iteration NIPS 2018
Planning and Learning with Stochastic Action Sets IJCAI 2018
Smoothed Action Value Functions for Learning Gaussian Policies ICML 2018
Multi-view Matrix Factorization for Linear Dynamical System Estimation NIPS 2017
Generalized Conditional Gradient for Sparse Estimation JMLR 2017
Bridging the Gap Between Value and Policy Based Reinforcement Learning NIPS 2017
Logistic Markov Decision Processes IJCAI 2017
Reward Augmented Maximum Likelihood for Neural Structured Prediction NIPS 2016
Deep Learning Games NIPS 2016
Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016
Scalable and Sound Low-Rank Tensor Learning AISTATS 2016
Variance Reduction via Antithetic Markov Chains AISTATS 2015
Correcting Covariate Shift with the Frank-Wolfe Algorithm IJCAI 2015
Semi-Supervised Zero-Shot Classification With Label Representation Learning ICCV 2015
Embedding Inference for Structured Multilabel Prediction NIPS 2015
Adaptive Monte Carlo via Bandit Allocation ICML 2014
Convex Deep Learning via Normalized Kernels NIPS 2014
Characterizing the Representer Theorem ICML 2013
Learning a Metric Space for Neighbourhood Topology Estimation: Application to Manifold Learning ACML 2013
Polar Operators for Structured Sparse Estimation NIPS 2013
Convex Two-Layer Modeling NIPS 2013
A Polynomial-time Form of Robust Regression NIPS 2012
Generalized Optimal Reverse Prediction AISTATS 2012
Convex Multi-view Subspace Learning NIPS 2012
Accelerated Training for Matrix-norm Regularization: A Boosting Approach NIPS 2012
Relaxed Clipping: A Global Training Method for Robust Regression and Classification NIPS 2010
Improved Natural Language Learning via Variance-Regularization Support Vector Machines CONLL 2010
Convex Relaxation of Mixture Regression with Efficient Algorithms NIPS 2009
A General Projection Property for Distribution Families NIPS 2009
Semi-Supervised Convex Training for Dependency Parsing ACL 2008
Convex Relaxations of Latent Variable Training NIPS 2007
Stable Dual Dynamic Programming NIPS 2007
Discriminative Batch Mode Active Learning NIPS 2007
Improved Large Margin Dependency Parsing via Local Constraints and Laplacian Regularization CONLL 2006
Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling ACL 2006
Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields NIPS 2006
implicit Online Learning with Kernels NIPS 2006
Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling COLING 2006
Language and Task Independent Text Categorization with Simple Language Models NAACL 2003
Language Independent Authorship Attribution with Character Level N-Grams EACL 2003
Investigating the Relationship between Word Segmentation Performance and Retrieval Performance in Chinese IR COLING 2002