← Authors

John Langford

66 papers · 2004–2025 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (21) 🌍 Conference Polyglot (9) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (25) 🌟 Keyword Trendsetter Combo (6) 🏠 Conference Loyalist (22) πŸ† Grand Slam 🀝 Dynamic Duo (22) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ”¬ Deep Specialist (18) πŸ† Keyword Champion ⚑ Prolific Year (5) πŸ“ˆ Trend Setter πŸ’Ž Century Club (66) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (99) πŸ”₯ Unstoppable (12)

Conferences

NIPS (22) ICML (19) JMLR (8) COLT (6) ICLR (6) AISTATS (2) AAAI (1) EMNLP (1) NAACL (1)

Top co-authors

Alekh Agarwal (22) Akshay Krishnamurthy (19) Hal Daume III (10) Dipendra Misra (8) Paul Mineiro (7) Chicheng Zhang (6) Alina Beygelzimer (6) Lihong Li (5) Daniel J. Hsu (5) Nan Jiang (5)

Research topics

Methods (1)

Keywords

contextual bandit (17) online learning (14) regret bound (12) sample complexity (7) reinforcement learning (7) active learning (6) supervised learning (5) policy learning (5) policy optimization (4) cost-sensitive classification (4) sample-efficient learning (3) multiclass classification (3) representation learning (3) logarithmic time (3) continuous action (3) online algorithm (3) convex loss (3) visual observation (2) l1 regularization (2) agnostic learning (2)

Papers

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