John Langford

	2009
70		Alina Beygelzimer, John Langford, Pradeep Ravikumar: Error-Correcting Tournaments. ALT 2009: 247-262
69		Kilian Weinberger, Anirban Dasgupta, John Langford, Alexander J. Smola, Josh Attenberg: Feature hashing for large scale multitask learning. ICML 2009: 140
68		Alina Beygelzimer, John Langford, Bianca Zadrozny: Tutorial summary: Reductions in machine learning. ICML 2009: 172
67		Sanjoy Dasgupta, John Langford: Tutorial summary: Active learning. ICML 2009: 178
66		Alina Beygelzimer, Sanjoy Dasgupta, John Langford: Importance weighted active learning. ICML 2009: 7
65		John Langford, Ruslan Salakhutdinov, Tong Zhang: Learning nonlinear dynamic models. ICML 2009: 75
64		Alina Beygelzimer, John Langford: The offset tree for learning with partial labels. KDD 2009: 129-138
63		Daniel Hsu, Sham M. Kakade, John Langford, Tong Zhang: Multi-Label Prediction via Compressed Sensing CoRR abs/0902.1284: (2009)
62		Kilian Weinberger, Anirban Dasgupta, Josh Attenberg, John Langford, Alex J. Smola: Feature Hashing for Large Scale Multitask Learning CoRR abs/0902.2206: (2009)
61		Alina Beygelzimer, John Langford, Pradeep Ravikumar: Error-Correcting Tournaments CoRR abs/0902.3176: (2009)
60		Alina Beygelzimer, John Langford, Yuri Lifshits, Gregory B. Sorkin, Alexander L. Strehl: Conditional Probability Tree Estimation Analysis and Algorithms CoRR abs/0903.4217: (2009)
59		John Langford, Ruslan Salakhutdinov, Tong Zhang: Learning Nonlinear Dynamic Models CoRR abs/0905.3369: (2009)
58		Hal Daumé III, John Langford, Daniel Marcu: Search-based Structured Prediction CoRR abs/0907.0786: (2009)
57		Nicholas J. Hopper, Luis von Ahn, John Langford: Provably Secure Steganography. IEEE Trans. Computers 58(5): 662-676 (2009)
56		Maria-Florina Balcan, Alina Beygelzimer, John Langford: Agnostic active learning. J. Comput. Syst. Sci. 75(1): 78-89 (2009)
	2008
55		Nicolas S. Lambert, John Langford, Jennifer Wortman, Yiling Chen, Daniel M. Reeves, Yoav Shoham, David M. Pennock: Self-financed wagering mechanisms for forecasting. ACM Conference on Electronic Commerce 2008: 170-179
54		John Langford, Alexander L. Strehl, Jennifer Wortman: Exploration scavenging. ICML 2008: 528-535
53		Sharad Goel, John Langford, Alexander L. Strehl: Predictive Indexing for Fast Search. NIPS 2008: 505-512
52		John Langford, Lihong Li, Tong Zhang: Sparse Online Learning via Truncated Gradient. NIPS 2008: 905-912
51		John Langford, Lihong Li, Tong Zhang: Sparse Online Learning via Truncated Gradient CoRR abs/0806.4686: (2008)
50		Alina Beygelzimer, John Langford: The Offset Tree for Learning with Partial Labels CoRR abs/0812.4044: (2008)
49		Alina Beygelzimer, Sanjoy Dasgupta, John Langford: Importance Weighted Active Learning CoRR abs/0812.4952: (2008)
48		Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin: Robust reductions from ranking to classification. Machine Learning 72(1-2): 139-153 (2008)
	2007
47		Maria-Florina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, Gregory B. Sorkin: Robust Reductions from Ranking to Classification. COLT 2007: 604-619
46		John Langford, Tong Zhang: The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information. NIPS 2007
45		Jennifer Wortman, Yevgeniy Vorobeychik, Lihong Li, John Langford: Maintaining Equilibria During Exploration in Sponsored Search Auctions. WINE 2007: 119-130
44		Peter Grünwald, John Langford: Suboptimal behavior of Bayes and MDL in classification under misspecification. Machine Learning 66(2-3): 119-149 (2007)
	2006
43		Jacob Abernethy, John Langford, Manfred K. Warmuth: Continuous Experts and the Binning Algorithm. COLT 2006: 544-558
42		Maria-Florina Balcan, Alina Beygelzimer, John Langford: Agnostic active learning. ICML 2006: 65-72
41		Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman: PAC model-free reinforcement learning. ICML 2006: 881-888
40		Alina Beygelzimer, Sham Kakade, John Langford: Cover trees for nearest neighbor. ICML 2006: 97-104
39		Naoki Abe, Bianca Zadrozny, John Langford: Outlier detection by active learning. KDD 2006: 504-509
38		John Langford, Roberto Oliveira, Bianca Zadrozny: Predicting Conditional Quantiles via Reduction to Classification. UAI 2006
37		John Langford, Jeffrey Roy: E-government and public-private partnerships in Canada: when failure is no longer an option. IJEB 4(2): 118-135 (2006)
	2005
36		Alina Beygelzimer, John Langford, Bianca Zadrozny: Weighted One-Against-All. AAAI 2005: 720-725
35		John Langford, Alina Beygelzimer: Sensitive Error Correcting Output Codes. COLT 2005: 158-172
34		John Langford: The Cross Validation Problem. COLT 2005: 687-688
33		Matti Kääriäinen, John Langford: A comparison of tight generalization error bounds. ICML 2005: 409-416
32		John Langford, Bianca Zadrozny: Relating reinforcement learning performance to classification performance. ICML 2005: 473-480
31		Alina Beygelzimer, Varsha Dani, Thomas P. Hayes, John Langford, Bianca Zadrozny: Error limiting reductions between classification tasks. ICML 2005: 49-56
30		Luis von Ahn, Nicholas J. Hopper, John Langford: Covert two-party computation. STOC 2005: 513-522
29		John Langford: Tutorial on Practical Prediction Theory for Classification. Journal of Machine Learning Research 6: 273-306 (2005)
	2004
28		Peter Grünwald, John Langford: Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification. COLT 2004: 331-347
27		Naoki Abe, Bianca Zadrozny, John Langford: An iterative method for multi-class cost-sensitive learning. KDD 2004: 3-11
26		Arindam Banerjee, John Langford: An objective evaluation criterion for clustering. KDD 2004: 515-520
25		Peter Grünwald, John Langford: Suboptimal behaviour of Bayes and MDL in classification under misspecification CoRR math.ST/0406221: (2004)
24		Luis von Ahn, Manuel Blum, John Langford: Telling humans and computers apart automatically. Commun. ACM 47(2): 56-60 (2004)
23		Alina Beygelzimer, Varsha Dani, Thomas P. Hayes, John Langford: Reductions Between Classification Tasks Electronic Colloquium on Computational Complexity (ECCC)(077): (2004)
22		John Langford, David A. McAllester: Computable Shell Decomposition Bounds. Journal of Machine Learning Research 5: 529-547 (2004)
	2003
21		Sham Kakade, Michael J. Kearns, John Langford, Luis E. Ortiz: Correlated equilibria in graphical games. ACM Conference on Electronic Commerce 2003: 42-47
20		Avrim Blum, John Langford: PAC-MDL Bounds. COLT 2003: 344-357
19		Luis von Ahn, Manuel Blum, Nicholas J. Hopper, John Langford: CAPTCHA: Using Hard AI Problems for Security. EUROCRYPT 2003: 294-311
18		Bianca Zadrozny, John Langford, Naoki Abe: Cost-Sensitive Learning by Cost-Proportionate Example Weighting. ICDM 2003: 435-
17		Sham Kakade, Michael J. Kearns, John Langford: Exploration in Metric State Spaces. ICML 2003: 306-312
16		John Langford, Avrim Blum: Microchoice Bounds and Self Bounding Learning Algorithms. Machine Learning 51(2): 165-179 (2003)
	2002
15		Nicholas J. Hopper, John Langford, Luis von Ahn: Provably Secure Steganography. CRYPTO 2002: 77-92
14		Sham Kakade, John Langford: Approximately Optimal Approximate Reinforcement Learning. ICML 2002: 267-274
13		John Langford: Combining Trainig Set and Test Set Bounds. ICML 2002: 331-338
12		John Langford, Martin Zinkevich, Sham Kakade: Competitive Analysis of the Explore/Exploit Tradeoff. ICML 2002: 339-346
11		John Langford, John Shawe-Taylor: PAC-Bayes & Margins. NIPS 2002: 423-430
	2001
10		John Langford, Matthias Seeger, Nimrod Megiddo: An Improved Predictive Accuracy Bound for Averaging Classifiers. ICML 2001: 290-297
9		John Langford, Rich Caruana: (Not) Bounding the True Error. NIPS 2001: 809-816
8		Sebastian Thrun, John Langford, Vandi Verma: Risk Sensitive Particle Filters. NIPS 2001: 961-968
	2000
7		John Langford, David A. McAllester: Computable Shell Decomposition Bounds. COLT 2000: 25-34
6		Joseph O'Sullivan, John Langford, Rich Caruana, Avrim Blum: FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness. ICML 2000: 703-710
	1999
5		Avrim Blum, Adam Kalai, John Langford: Beating the Hold-Out: Bounds for K-fold and Progressive Cross-Validation. COLT 1999: 203-208
4		John Langford, Avrim Blum: Microchoice Bounds and Self Bounding Learning Algorithms. COLT 1999: 209-214
3		Avrim Blum, John Langford: Probabilistic Planning in the Graphplan Framework. ECP 1999: 319-332
2		Sebastian Thrun, John Langford, Dieter Fox: Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes. ICML 1999: 415-424
	1998
1		Avrim Blum, Carl Burch, John Langford: On Learning Monotone Boolean Functions. FOCS 1998: 408-415

Coauthor Index

1	Naoki Abe	[18] [27] [39]
2	Jacob Abernethy	[43]
3	Luis von Ahn	[15] [19] [24] [30] [57]
4	Josh Attenberg	[62] [69]
5	Maria-Florina Balcan (Maria-Florina Popa)	[42] [47] [48] [56]
6	Arindam Banerjee	[26]
7	Nikhil Bansal	[47] [48]
8	Alina Beygelzimer	[23] [31] [35] [36] [40] [42] [47] [48] [49] [50] [56] [60] [61] [64] [66] [68] [70]
9	Avrim Blum	[1] [3] [4] [5] [6] [16] [20]
10	Manuel Blum	[19] [24]
11	Carl Burch	[1]
12	Rich Caruana	[6] [9]
13	Yiling Chen	[55]
14	Don Coppersmith	[47] [48]
15	Varsha Dani	[23] [31]
16	Anirban Dasgupta	[62] [69]
17	Sanjoy Dasgupta	[49] [66] [67]
18	Hal Daumé III	[58]
19	Dieter Fox	[2]
20	Sharad Goel	[53]
21	Peter Grünwald (Peter D. Grünwald, Peter Grunwald)	[25] [28] [44]
22	Thomas P. Hayes	[23] [31]
23	Nicholas J. Hopper	[15] [19] [30] [57]
24	Daniel Hsu	[63]
25	Matti Kääriäinen	[33]
26	Sham M. Kakade (Sham Kakade)	[12] [14] [17] [21] [40] [63]
27	Adam Tauman Kalai (Adam Kalai)	[5]
28	Michael J. Kearns	[17] [21]
29	Nicolas S. Lambert	[55]
30	Lihong Li	[41] [45] [51] [52]
31	Yuri Lifshits	[60]
32	Michael L. Littman	[41]
33	Daniel Marcu	[58]
34	David A. McAllester	[7] [22]
35	Nimrod Megiddo	[10]
36	Joseph O'Sullivan	[6]
37	Roberto Oliveira	[38]
38	Luis E. Ortiz	[21]
39	David M. Pennock (David Pennock)	[55]
40	Pradeep Ravikumar	[61] [70]
41	Daniel M. Reeves	[55]
42	Jeffrey Roy	[37]
43	Ruslan Salakhutdinov	[59] [65]
44	Matthias Seeger	[10]
45	John Shawe-Taylor	[11]
46	Yoav Shoham	[55]
47	Alexander J. Smola (Alex J. Smola)	[62] [69]
48	Gregory B. Sorkin	[47] [48] [60]
49	Alexander L. Strehl	[41] [53] [54] [60]
50	Sebastian Thrun	[2] [8]
51	Vandi Verma	[8]
52	Yevgeniy Vorobeychik	[45]
53	Manfred K. Warmuth	[43]
54	Kilian Weinberger	[62] [69]
55	Eric Wiewiora	[41]
56	Jennifer Wortman	[45] [54] [55]
57	Bianca Zadrozny	[18] [27] [31] [32] [36] [38] [39] [68]
58	Tong Zhang	[46] [51] [52] [59] [63] [65]
59	Martin Zinkevich	[12]

Colors in the list of coauthors