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## Search the dblp DataBase
John Langford:
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## Publications of Author- Alina Beygelzimer, John Langford, Bianca Zadrozny
**Weighted One-Against-All.**[Citation Graph (0, 0)][DBLP] AAAI, 2005, pp:720-725 [Conf] - Jacob Abernethy, John Langford, Manfred K. Warmuth
**Continuous Experts and the Binning Algorithm.**[Citation Graph (0, 0)][DBLP] COLT, 2006, pp:544-558 [Conf] - Avrim Blum, Adam Kalai, John Langford
**Beating the Hold-Out: Bounds for K-fold and Progressive Cross-Validation.**[Citation Graph (0, 0)][DBLP] COLT, 1999, pp:203-208 [Conf] - Avrim Blum, John Langford
**PAC-MDL Bounds.**[Citation Graph (0, 0)][DBLP] COLT, 2003, pp:344-357 [Conf] - Peter Grünwald, John Langford
**Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification.**[Citation Graph (0, 0)][DBLP] COLT, 2004, pp:331-347 [Conf] - John Langford
**The Cross Validation Problem.**[Citation Graph (0, 0)][DBLP] COLT, 2005, pp:687-688 [Conf] - John Langford, Alina Beygelzimer
**Sensitive Error Correcting Output Codes.**[Citation Graph (0, 0)][DBLP] COLT, 2005, pp:158-172 [Conf] - John Langford, Avrim Blum
**Microchoice Bounds and Self Bounding Learning Algorithms.**[Citation Graph (0, 0)][DBLP] COLT, 1999, pp:209-214 [Conf] - John Langford, David A. McAllester
**Computable Shell Decomposition Bounds.**[Citation Graph (0, 0)][DBLP] COLT, 2000, pp:25-34 [Conf] - Nicholas J. Hopper, John Langford, Luis von Ahn
**Provably Secure Steganography.**[Citation Graph (0, 0)][DBLP] CRYPTO, 2002, pp:77-92 [Conf] - Avrim Blum, John Langford
**Probabilistic Planning in the Graphplan Framework.**[Citation Graph (0, 0)][DBLP] ECP, 1999, pp:319-332 [Conf] - Luis von Ahn, Manuel Blum, Nicholas J. Hopper, John Langford
**CAPTCHA: Using Hard AI Problems for Security.**[Citation Graph (0, 0)][DBLP] EUROCRYPT, 2003, pp:294-311 [Conf] - Avrim Blum, Carl Burch, John Langford
**On Learning Monotone Boolean Functions.**[Citation Graph (0, 0)][DBLP] FOCS, 1998, pp:408-415 [Conf] - Bianca Zadrozny, John Langford, Naoki Abe
**Cost-Sensitive Learning by Cost-Proportionate Example Weighting.**[Citation Graph (0, 0)][DBLP] ICDM, 2003, pp:435-0 [Conf] - Maria-Florina Balcan, Alina Beygelzimer, John Langford
**Agnostic active learning.**[Citation Graph (0, 0)][DBLP] ICML, 2006, pp:65-72 [Conf] - Alina Beygelzimer, Varsha Dani, Tom Hayes, John Langford, Bianca Zadrozny
**Error limiting reductions between classification tasks.**[Citation Graph (0, 0)][DBLP] ICML, 2005, pp:49-56 [Conf] - Alina Beygelzimer, Sham Kakade, John Langford
**Cover trees for nearest neighbor.**[Citation Graph (0, 0)][DBLP] ICML, 2006, pp:97-104 [Conf] - Matti Kääriäinen, John Langford
**A comparison of tight generalization error bounds.**[Citation Graph (0, 0)][DBLP] ICML, 2005, pp:409-416 [Conf] - Sham Kakade, Michael J. Kearns, John Langford
**Exploration in Metric State Spaces.**[Citation Graph (0, 0)][DBLP] ICML, 2003, pp:306-312 [Conf] - Sham Kakade, John Langford
**Approximately Optimal Approximate Reinforcement Learning.**[Citation Graph (0, 0)][DBLP] ICML, 2002, pp:267-274 [Conf] - John Langford
**Combining Trainig Set and Test Set Bounds.**[Citation Graph (0, 0)][DBLP] ICML, 2002, pp:331-338 [Conf] - John Langford, Matthias Seeger, Nimrod Megiddo
**An Improved Predictive Accuracy Bound for Averaging Classifiers.**[Citation Graph (0, 0)][DBLP] ICML, 2001, pp:290-297 [Conf] - John Langford, Bianca Zadrozny
**Relating reinforcement learning performance to classification performance.**[Citation Graph (0, 0)][DBLP] ICML, 2005, pp:473-480 [Conf] - John Langford, Martin Zinkevich, Sham Kakade
**Competitive Analysis of the Explore/Exploit Tradeoff.**[Citation Graph (0, 0)][DBLP] ICML, 2002, pp:339-346 [Conf] - Joseph O'Sullivan, John Langford, Rich Caruana, Avrim Blum
**FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness.**[Citation Graph (0, 0)][DBLP] ICML, 2000, pp:703-710 [Conf] - Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman
**PAC model-free reinforcement learning.**[Citation Graph (0, 0)][DBLP] ICML, 2006, pp:881-888 [Conf] - Sebastian Thrun, John Langford, Dieter Fox
**Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes.**[Citation Graph (0, 0)][DBLP] ICML, 1999, pp:415-424 [Conf] - Naoki Abe, Bianca Zadrozny, John Langford
**An iterative method for multi-class cost-sensitive learning.**[Citation Graph (0, 0)][DBLP] KDD, 2004, pp:3-11 [Conf] - Naoki Abe, Bianca Zadrozny, John Langford
**Outlier detection by active learning.**[Citation Graph (0, 0)][DBLP] KDD, 2006, pp:504-509 [Conf] - Arindam Banerjee, John Langford
**An objective evaluation criterion for clustering.**[Citation Graph (0, 0)][DBLP] KDD, 2004, pp:515-520 [Conf] - John Langford, Rich Caruana
**(Not) Bounding the True Error.**[Citation Graph (0, 0)][DBLP] NIPS, 2001, pp:809-816 [Conf] - John Langford, John Shawe-Taylor
**PAC-Bayes & Margins.**[Citation Graph (0, 0)][DBLP] NIPS, 2002, pp:423-430 [Conf] - Sebastian Thrun, John Langford, Vandi Verma
**Risk Sensitive Particle Filters.**[Citation Graph (0, 0)][DBLP] NIPS, 2001, pp:961-968 [Conf] - Sham Kakade, Michael J. Kearns, John Langford, Luis E. Ortiz
**Correlated equilibria in graphical games.**[Citation Graph (0, 0)][DBLP] ACM Conference on Electronic Commerce, 2003, pp:42-47 [Conf] - Luis von Ahn, Nicholas J. Hopper, John Langford
**Covert two-party computation.**[Citation Graph (0, 0)][DBLP] STOC, 2005, pp:513-522 [Conf] - Luis von Ahn, Manuel Blum, John Langford
**Telling humans and computers apart automatically.**[Citation Graph (0, 0)][DBLP] Commun. ACM, 2004, v:47, n:2, pp:56-60 [Journal] - Peter Grünwald, John Langford
**Suboptimal behaviour of Bayes and MDL in classification under misspecification**[Citation Graph (0, 0)][DBLP] CoRR, 2004, v:0, n:, pp:- [Journal] - Alina Beygelzimer, Varsha Dani, Thomas P. Hayes, John Langford
**Reductions Between Classification Tasks**[Citation Graph (0, 0)][DBLP] Electronic Colloquium on Computational Complexity (ECCC), 2004, v:, n:077, pp:- [Journal] - John Langford, David A. McAllester
**Computable Shell Decomposition Bounds.**[Citation Graph (0, 0)][DBLP] Journal of Machine Learning Research, 2004, v:5, n:, pp:529-547 [Journal] - John Langford
**Tutorial on Practical Prediction Theory for Classification.**[Citation Graph (0, 0)][DBLP] Journal of Machine Learning Research, 2005, v:6, n:, pp:273-306 [Journal] - John Langford, Avrim Blum
**Microchoice Bounds and Self Bounding Learning Algorithms.**[Citation Graph (0, 0)][DBLP] Machine Learning, 2003, v:51, n:2, pp:165-179 [Journal] - Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin
**Robust Reductions from Ranking to Classification.**[Citation Graph (0, 0)][DBLP] COLT, 2007, pp:604-619 [Conf] - John Langford, Roberto Oliveira, Bianca Zadrozny
**Predicting Conditional Quantiles via Reduction to Classification.**[Citation Graph (0, 0)][DBLP] UAI, 2006, pp:- [Conf] - Peter Grünwald, John Langford
**Suboptimal behavior of Bayes and MDL in classification under misspecification.**[Citation Graph (0, 0)][DBLP] Machine Learning, 2007, v:66, n:2-3, pp:119-149 [Journal] **Error-Correcting Tournaments.**[Citation Graph (, )][DBLP]**Exploration scavenging.**[Citation Graph (, )][DBLP]**Tutorial summary: Reductions in machine learning.**[Citation Graph (, )][DBLP]**Learning nonlinear dynamic models.**[Citation Graph (, )][DBLP]**Tutorial summary: Active learning.**[Citation Graph (, )][DBLP]**Importance weighted active learning.**[Citation Graph (, )][DBLP]**Feature hashing for large scale multitask learning.**[Citation Graph (, )][DBLP]**The offset tree for learning with partial labels.**[Citation Graph (, )][DBLP]**The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information.**[Citation Graph (, )][DBLP]**Sparse Online Learning via Truncated Gradient.**[Citation Graph (, )][DBLP]**Predictive Indexing for Fast Search.**[Citation Graph (, )][DBLP]**Self-financed wagering mechanisms for forecasting.**[Citation Graph (, )][DBLP]**Maintaining Equilibria During Exploration in Sponsored Search Auctions.**[Citation Graph (, )][DBLP]**A contextual-bandit approach to personalized news article recommendation.**[Citation Graph (, )][DBLP]**Sparse Online Learning via Truncated Gradient**[Citation Graph (, )][DBLP]**The Offset Tree for Learning with Partial Labels**[Citation Graph (, )][DBLP]**Importance Weighted Active Learning**[Citation Graph (, )][DBLP]**Multi-Label Prediction via Compressed Sensing**[Citation Graph (, )][DBLP]**Feature Hashing for Large Scale Multitask Learning**[Citation Graph (, )][DBLP]**Error-Correcting Tournaments**[Citation Graph (, )][DBLP]**Conditional Probability Tree Estimation Analysis and Algorithms**[Citation Graph (, )][DBLP]**Learning Nonlinear Dynamic Models**[Citation Graph (, )][DBLP]**Search-based Structured Prediction**[Citation Graph (, )][DBLP]**An Optimal High Probability Algorithm for the Contextual Bandit Problem**[Citation Graph (, )][DBLP]**Learning from Logged Implicit Exploration Data**[Citation Graph (, )][DBLP]**A Contextual-Bandit Approach to Personalized News Article Recommendation**[Citation Graph (, )][DBLP]**An Unbiased, Data-Driven, Offline Evaluation Method of Contextual Bandit Algorithms**[Citation Graph (, )][DBLP]**Agnostic Active Learning Without Constraints**[Citation Graph (, )][DBLP]
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