John Langford

The Belief State Transformer ICLR 2025 Towards Principled Representation Learning from Videos for Reinforcement Learning ICLR 2024 Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization NIPS 2024 Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss ICML 2024 PcLast: Discovering Plannable Continuous Latent States ICML 2024 Principled Offline RL in the Presence of Rich Exogenous Information ICML 2023 Streaming Active Learning with Deep Neural Networks ICML 2023 Better Parameter-Free Stochastic Optimization with ODE Updates for Coin-Betting AAAI 2022 Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning ICML 2022 Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information COLT 2022 Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics ICLR 2022 Interaction-Grounded Learning with Action-Inclusive Feedback NIPS 2022 Contextual Bandits with Large Action Spaces: Made Practical ICML 2022 Interaction-Grounded Learning ICML 2021 Provable Rich Observation Reinforcement Learning with Combinatorial Latent States ICLR 2021 ChaCha for Online AutoML ICML 2021 A Contextual Bandit Bake-off JMLR 2021 Efficient Contextual Bandits with Continuous Actions NIPS 2020 Empirical Likelihood for Contextual Bandits NIPS 2020 Learning the Linear Quadratic Regulator from Nonlinear Observations NIPS 2020 Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting JMLR 2020 Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds ICLR 2020 Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning ICML 2020 Active Learning for Cost-Sensitive Classification JMLR 2019 Contextual Memory Trees ICML 2019 Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback ICML 2019 Efficient Forward Architecture Search NIPS 2019 Contextual bandits with continuous actions: Smoothing, zooming, and adapting COLT 2019 Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches COLT 2019 Provably efficient RL with Rich Observations via Latent State Decoding ICML 2019 A Reductions Approach to Fair Classification ICML 2018 Efficient Contextual Bandits in Non-stationary Worlds COLT 2018 Learning Deep ResNet Blocks Sequentially using Boosting Theory ICML 2018 On Oracle-Efficient PAC RL with Rich Observations NIPS 2018 Residual Loss Prediction: Reinforcement Learning With No Incremental Feedback ICLR 2018 Open Problem: First-Order Regret Bounds for Contextual Bandits COLT 2017 Mapping Instructions and Visual Observations to Actions with Reinforcement Learning EMNLP 2017 Off-policy evaluation for slate recommendation NIPS 2017 Logarithmic Time One-Against-Some ICML 2017 Contextual Decision Processes with low Bellman rank are PAC-Learnable ICML 2017 Active Learning for Cost-Sensitive Classification ICML 2017 A Credit Assignment Compiler for Joint Prediction NIPS 2016 Efficient Second Order Online Learning by Sketching NIPS 2016 PAC Reinforcement Learning with Rich Observations NIPS 2016 Search Improves Label for Active Learning NIPS 2016 Hands-on Learning to Search for Structured Prediction NAACL 2015 Efficient and Parsimonious Agnostic Active Learning NIPS 2015 Logarithmic Time Online Multiclass prediction NIPS 2015 Learning to Search Better than Your Teacher ICML 2015 Resourceful Contextual Bandits COLT 2014 A Reliable Effective Terascale Linear Learning System JMLR 2014 Scalable Non-linear Learning with Adaptive Polynomial Expansions NIPS 2014 Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits ICML 2014 Contextual Bandit Learning with Predictable Rewards AISTATS 2012 Contextual Bandit Algorithms with Supervised Learning Guarantees AISTATS 2011 Agnostic Active Learning Without Constraints NIPS 2010 Learning from Logged Implicit Exploration Data NIPS 2010 Multi-Label Prediction via Compressed Sensing NIPS 2009 Slow Learners are Fast NIPS 2009 Sparse Online Learning via Truncated Gradient JMLR 2009 Hash Kernels for Structured Data JMLR 2009 Sparse Online Learning via Truncated Gradient NIPS 2008 Predictive Indexing for Fast Search NIPS 2008 The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information NIPS 2007 Tutorial on Practical Prediction Theory for Classification JMLR 2005 Computable Shell Decomposition Bounds JMLR 2004