John Langford

Affiliations:
  • Microsoft Research, USA


According to our database1, John Langford authored at least 172 papers between 1998 and 2024.

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Bibliography

2024
Learning to Achieve Goals with Belief State Transformers.
CoRR, 2024

EnsemW2S: Can an Ensemble of LLMs be Leveraged to Obtain a Stronger LLM?
CoRR, 2024

Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization.
CoRR, 2024

Video Occupancy Models.
CoRR, 2024

Position Paper: Agent AI Towards a Holistic Intelligence.
CoRR, 2024

Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

PcLast: Discovering Plannable Continuous Latent States.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Principled Representation Learning from Videos for Reinforcement Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models.
Trans. Mach. Learn. Res., 2023

Autocalibrating Gaze Tracking: A Demonstration through Gaze Typing.
CoRR, 2023

Streaming Active Learning with Deep Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

Principled Offline RL in the Presence of Rich Exogenous Information.
Proceedings of the International Conference on Machine Learning, 2023

2022
Towards Data-Driven Offline Simulations for Online Reinforcement Learning.
CoRR, 2022

Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information.
CoRR, 2022

Eigen Memory Trees.
CoRR, 2022

Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models.
CoRR, 2022

Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization.
CoRR, 2022

Interaction-Grounded Learning with Action-Inclusive Feedback.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Contextual Bandits with Large Action Spaces: Made Practical.
Proceedings of the International Conference on Machine Learning, 2022

Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning.
Proceedings of the International Conference on Machine Learning, 2022

Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Better Parameter-Free Stochastic Optimization with ODE Updates for Coin-Betting.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
A Contextual Bandit Bake-off.
J. Mach. Learn. Res., 2021

Provable RL with Exogenous Distractors via Multistep Inverse Dynamics.
CoRR, 2021

Interaction-Grounded Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

ChaCha for Online AutoML.
Proceedings of the 38th International Conference on Machine Learning, 2021

Provable Rich Observation Reinforcement Learning with Combinatorial Latent States.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting.
J. Mach. Learn. Res., 2020

PACT: Privacy-Sensitive Protocols And Mechanisms for Mobile Contact Tracing.
IEEE Data Eng. Bull., 2020

Resonance: Replacing Software Constants with Context-Aware Models in Real-time Communication.
CoRR, 2020

PACT: Privacy Sensitive Protocols and Mechanisms for Mobile Contact Tracing.
CoRR, 2020

Federated Residual Learning.
CoRR, 2020

Learning the Linear Quadratic Regulator from Nonlinear Observations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Contextual Bandits with Continuous Actions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Empirical Likelihood for Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Active Learning for Cost-Sensitive Classification.
J. Mach. Learn. Res., 2019

Efficient Forward Architecture Search.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback.
Proceedings of the 36th International Conference on Machine Learning, 2019

Contextual Memory Trees.
Proceedings of the 36th International Conference on Machine Learning, 2019

Provably efficient RL with Rich Observations via Latent State Decoding.
Proceedings of the 36th International Conference on Machine Learning, 2019

Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches.
Proceedings of the Conference on Learning Theory, 2019

2018
Model-Based Reinforcement Learning in Contextual Decision Processes.
CoRR, 2018

On Polynomial Time PAC Reinforcement Learning with Rich Observations.
CoRR, 2018

Practical Evaluation and Optimization of Contextual Bandit Algorithms.
CoRR, 2018

On Oracle-Efficient PAC RL with Rich Observations.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Deep ResNet Blocks Sequentially using Boosting Theory.
Proceedings of the 35th International Conference on Machine Learning, 2018

A Reductions Approach to Fair Classification.
Proceedings of the 35th International Conference on Machine Learning, 2018

Residual Loss Prediction: Reinforcement Learning With No Incremental Feedback.
Proceedings of the 6th International Conference on Learning Representations, 2018

Efficient Contextual Bandits in Non-stationary Worlds.
Proceedings of the Conference On Learning Theory, 2018

2017
Efficient Exploration in Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Efficient Contextual Bandits in Non-stationary Worlds.
CoRR, 2017

Off-policy evaluation for slate recommendation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Contextual Decision Processes with low Bellman rank are PAC-Learnable.
Proceedings of the 34th International Conference on Machine Learning, 2017

Logarithmic Time One-Against-Some.
Proceedings of the 34th International Conference on Machine Learning, 2017

Mapping Instructions and Visual Observations to Actions with Reinforcement Learning.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Open Problem: First-Order Regret Bounds for Contextual Bandits.
Proceedings of the 30th Conference on Learning Theory, 2017

Contextual reinforcement learning.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
Learning Reductions That Really Work.
Proc. IEEE, 2016

Efficient Second Order Online Learning via Sketching.
CoRR, 2016

Contextual-MDPs for PAC-Reinforcement Learning with Rich Observations.
CoRR, 2016

A Multiworld Testing Decision Service.
CoRR, 2016

The solution to AI, what real researchers do, and expectations for CS classrooms.
Commun. ACM, 2016

Efficient Second Order Online Learning by Sketching.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

PAC Reinforcement Learning with Rich Observations.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Credit Assignment Compiler for Joint Prediction.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Search Improves Label for Active Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
An axiomatic characterization of wagering mechanisms.
J. Econ. Theory, 2015

Doubly Robust Policy Evaluation and Optimization.
CoRR, 2015

Learning to Search for Dependencies.
CoRR, 2015

The arbitrariness of reviews, and advice for school administrators.
Commun. ACM, 2015

Efficient and Parsimonious Agnostic Active Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Logarithmic Time Online Multiclass prediction.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Hands-on Learning to Search for Structured Prediction.
Proceedings of the NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31, 2015

Learning to Search Better than Your Teacher.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
A reliable effective terascale linear learning system.
J. Mach. Learn. Res., 2014

Efficient programmable learning to search.
CoRR, 2014

Scalable Nonlinear Learning with Adaptive Polynomial Expansions.
CoRR, 2014

Finding a research job, and teaching CS in high school.
Commun. ACM, 2014

Scalable Non-linear Learning with Adaptive Polynomial Expansions.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits.
Proceedings of the 31th International Conference on Machine Learning, 2014

Resourceful Contextual Bandits.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Efficient Online Bootstrapping for Large Scale Learning.
CoRR, 2013

Para-active learning.
CoRR, 2013

Normalized Online Learning.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

2012
Bandits with Generalized Linear Models.
Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, 2012

Contextual Bandit Learning with Predictable Rewards.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Cloud control: voluntary admission control for intranet traffic management.
Inf. Syst. E Bus. Manag., 2012

Parallel machine learning on big data.
XRDS, 2012

Proceedings of the 29th International Conference on Machine Learning (ICML-12)
CoRR, 2012

Machine learning and algorithms; agile development.
Commun. ACM, 2012

Sample-efficient Nonstationary Policy Evaluation for Contextual Bandits.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Learning performance of prediction markets with Kelly bettors.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012

2011
Contextual Bandit Algorithms with Supervised Learning Guarantees.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Parallel Online Learning
CoRR, 2011

Conferences and video lectures; scientific educational games.
Commun. ACM, 2011

Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms.
Proceedings of the Forth International Conference on Web Search and Web Data Mining, 2011

Online Importance Weight Aware Updates.
Proceedings of the UAI 2011, 2011

Efficient Optimal Learning for Contextual Bandits.
Proceedings of the UAI 2011, 2011

Doubly Robust Policy Evaluation and Learning.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Efficient Exploration in Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Importance Weight Aware Gradient Updates
CoRR, 2010

An Unbiased, Data-Driven, Offline Evaluation Method of Contextual Bandit Algorithms
CoRR, 2010

Learning from Logged Implicit Exploration Data
CoRR, 2010

An Optimal High Probability Algorithm for the Contextual Bandit Problem
CoRR, 2010

Maintaining Equilibria During Exploration in Sponsored Search Auctions.
Algorithmica, 2010

A contextual-bandit approach to personalized news article recommendation.
Proceedings of the 19th International Conference on World Wide Web, 2010

Learning from Logged Implicit Exploration Data.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Agnostic Active Learning Without Constraints.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Robust Efficient Conditional Probability Estimation.
Proceedings of the COLT 2010, 2010

2009
Provably Secure Steganography.
IEEE Trans. Computers, 2009

Search-based structured prediction.
Mach. Learn., 2009

Hash Kernels for Structured Data.
J. Mach. Learn. Res., 2009

Hash Kernels.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Sparse Online Learning via Truncated Gradient.
J. Mach. Learn. Res., 2009

Agnostic active learning.
J. Comput. Syst. Sci., 2009

Conditional Probability Tree Estimation Analysis and Algorithms.
Proceedings of the UAI 2009, 2009

Slow Learners are Fast.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Multi-Label Prediction via Compressed Sensing.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

The offset tree for learning with partial labels.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Feature hashing for large scale multitask learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Learning nonlinear dynamic models.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Tutorial summary: Active learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Tutorial summary: Reductions in machine learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Importance weighted active learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Error-Correcting Tournaments.
Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009

2008
Robust reductions from ranking to classification.
Mach. Learn., 2008

Self-financed wagering mechanisms for forecasting.
Proceedings of the Proceedings 9th ACM Conference on Electronic Commerce (EC-2008), 2008

Predictive Indexing for Fast Search.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Exploration scavenging.
Proceedings of the Machine Learning, 2008

2007
Suboptimal behavior of Bayes and MDL in classification under misspecification.
Mach. Learn., 2007

The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Predicting Conditional Quantiles via Reduction to Classification.
Proceedings of the UAI '06, 2006

Outlier detection by active learning.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

PAC model-free reinforcement learning.
Proceedings of the Machine Learning, 2006

Cover trees for nearest neighbor.
Proceedings of the Machine Learning, 2006

Continuous Experts and the Binning Algorithm.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005
Tutorial on Practical Prediction Theory for Classification.
J. Mach. Learn. Res., 2005

Covert two-party computation.
Proceedings of the 37th Annual ACM Symposium on Theory of Computing, 2005

Relating reinforcement learning performance to classification performance.
Proceedings of the Machine Learning, 2005

A comparison of tight generalization error bounds.
Proceedings of the Machine Learning, 2005

Error limiting reductions between classification tasks.
Proceedings of the Machine Learning, 2005

Sensitive Error Correcting Output Codes.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

The Cross Validation Problem.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

Estimating Class Membership Probabilities using Classifier Learners.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

Weighted One-Against-All.
Proceedings of the Proceedings, 2005

2004
Computable Shell Decomposition Bounds.
J. Mach. Learn. Res., 2004

Reductions Between Classification Tasks
Electron. Colloquium Comput. Complex., 2004

Suboptimal behaviour of Bayes and MDL in classification under misspecification
CoRR, 2004

Telling humans and computers apart automatically.
Commun. ACM, 2004

An objective evaluation criterion for clustering.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

An iterative method for multi-class cost-sensitive learning.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

2003
Microchoice Bounds and Self Bounding Learning Algorithms.
Mach. Learn., 2003

Correlated equilibria in graphical games.
Proceedings of the Proceedings 4th ACM Conference on Electronic Commerce (EC-2003), 2003

Exploration in Metric State Spaces.
Proceedings of the Machine Learning, 2003

Cost-Sensitive Learning by Cost-Proportionate Example Weighting.
Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003

CAPTCHA: Using Hard AI Problems for Security.
Proceedings of the Advances in Cryptology, 2003

PAC-MDL Bounds.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
PAC-Bayes & Margins.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Competitive Analysis of the Explore/Exploit Tradeoff.
Proceedings of the Machine Learning, 2002

Combining Trainig Set and Test Set Bounds.
Proceedings of the Machine Learning, 2002

Approximately Optimal Approximate Reinforcement Learning.
Proceedings of the Machine Learning, 2002

2001
Risk Sensitive Particle Filters.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

(Not) Bounding the True Error.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

An Improved Predictive Accuracy Bound for Averaging Classifiers.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

1999
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes.
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999

Probabilistic Planning in the Graphplan Framework.
Proceedings of the Recent Advances in AI Planning, 5th European Conference on Planning, 1999

Beating the Hold-Out: Bounds for K-fold and Progressive Cross-Validation.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998
On Learning Monotone Boolean Functions.
Proceedings of the 39th Annual Symposium on Foundations of Computer Science, 1998


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