John Langford

According to our database1, John Langford authored at least 111 papers between 1998 and 2018.

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Bibliography

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

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

Active Learning for Cost-Sensitive Classification.
Proceedings of the 34th International Conference on Machine Learning, 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, BigData 2017, 2017

2016
Learning Reductions That Really Work.
Proceedings of the IEEE, 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. Economic Theory, 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.
Journal of Machine Learning Research, 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
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-Business Management, 2012

Parallel machine learning on big data.
ACM Crossroads, 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

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

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.
Machine Learning, 2009

Hash Kernels for Structured Data.
Journal of Machine Learning Research, 2009

Hash Kernels.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 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
Self-financed wagering mechanisms for forecasting.
Proceedings of the Proceedings 9th ACM Conference on Electronic Commerce (EC-2008), 2008

Sparse Online Learning via Truncated Gradient.
Proceedings of the Advances in Neural Information Processing Systems 21, 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
Maintaining Equilibria During Exploration in Sponsored Search Auctions.
Proceedings of the Internet and Network Economics, Third International Workshop, 2007

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

Robust Reductions from Ranking to Classification.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 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

Agnostic active learning.
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.
Journal of Machine Learning Research, 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
Reductions Between Classification Tasks
Electronic Colloquium on Computational Complexity (ECCC), 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

Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

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

Provably Secure Steganography.
Proceedings of the Advances in Cryptology, 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

Computable Shell Decomposition Bounds.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 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

Microchoice Bounds and Self Bounding Learning Algorithms.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 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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