John D. Lafferty

	2012
79		John D. Lafferty, Han Liu, Larry A. Wasserman: Sparse Nonparametric Graphical Models CoRR abs/1201.0794: (2012)
	2011
78		Kai Yu, Yuanqing Lin, John D. Lafferty: Learning image representations from the pixel level via hierarchical sparse coding. CVPR 2011: 1713-1720
77		Mladen Kolar, John D. Lafferty, Larry A. Wasserman: Union Support Recovery in Multi-task Learning. Journal of Machine Learning Research 12: 2415-2435 (2011)
76		Han Liu, Min Xu, Haijie Gu, Anupam Gupta, John D. Lafferty, Larry A. Wasserman: Forest Density Estimation. Journal of Machine Learning Research 12: 907-951 (2011)
	2010
75		John D. Lafferty, Christopher K. I. Williams, John Shawe-Taylor, Richard S. Zemel, Aron Culotta: 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, Vancouver, British Columbia, Canada. Curran Associates, Inc. 2010
74		Anupam Gupta, John D. Lafferty, Han Liu, Larry A. Wasserman, Min Xu: Forest Density Estimation. COLT 2010: 394-406
73		Han Liu, Xi Chen, John D. Lafferty, Larry A. Wasserman: Graph-Valued Regression. NIPS 2010: 1423-1431
72		Shuheng Zhou, John D. Lafferty, Larry A. Wasserman: Time varying undirected graphs. Machine Learning 80(2-3): 295-319 (2010)
	2009
71		Yoshua Bengio, Dale Schuurmans, John D. Lafferty, Christopher K. I. Williams, Aron Culotta: 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, Vancouver, British Columbia, Canada. Curran Associates, Inc. 2009
70		Kai Yu, John D. Lafferty, Shenghuo Zhu, Yihong Gong: Large-scale collaborative prediction using a nonparametric random effects model. ICML 2009: 149
69		Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gong: Fast nonparametric matrix factorization for large-scale collaborative filtering. SIGIR 2009: 211-218
68		Shuheng Zhou, John D. Lafferty, Larry A. Wasserman: Compressed and Privacy-Sensitive Sparse Regression. IEEE Transactions on Information Theory 55(2): 846-866 (2009)
67		Han Liu, John D. Lafferty, Larry A. Wasserman: The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs. Journal of Machine Learning Research 10: 2295-2328 (2009)
	2008
66		Shuheng Zhou, John D. Lafferty, Larry A. Wasserman: Time Varying Undirected Graphs. COLT 2008: 455-466
65		Han Liu, John D. Lafferty, Larry A. Wasserman: Nonparametric regression and classification with joint sparsity constraints. NIPS 2008: 969-976
	2007
64		Douglas L. Vail, Manuela M. Veloso, John D. Lafferty: Conditional random fields for activity recognition. AAMAS 2007: 235
63		Noah A. Smith, Douglas L. Vail, John D. Lafferty: Computationally Efficient M-Estimation of Log-Linear Structure Models. ACL 2007
62		Ramesh Nallapati, William W. Cohen, John D. Lafferty: Parallelized Variational EM for Latent Dirichlet Allocation: An Experimental Evaluation of Speed and Scalability. ICDM Workshops 2007: 349-354
61		Douglas L. Vail, John D. Lafferty, Manuela M. Veloso: Feature selection in conditional random fields for activity recognition. IROS 2007: 3379-3384
60		Ramesh Nallapati, Susan Ditmore, John D. Lafferty, Kin Ung: Multiscale topic tomography. KDD 2007: 520-529
59		Shuheng Zhou, John D. Lafferty, Larry A. Wasserman: Compressed Regression. NIPS 2007
58		Pradeep D. Ravikumar, Han Liu, John D. Lafferty, Larry A. Wasserman: SpAM: Sparse Additive Models. NIPS 2007
57		John D. Lafferty, Larry A. Wasserman: Statistical Analysis of Semi-Supervised Regression. NIPS 2007
56		Shuheng Zhou, John D. Lafferty, Larry A. Wasserman: Compressed Regression CoRR abs/0706.0534: (2007)
55		Han Liu, John D. Lafferty, Larry A. Wasserman: Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo. Journal of Machine Learning Research - Proceedings Track 2: 283-290 (2007)
	2006
54		David M. Blei, John D. Lafferty: Dynamic topic models. ICML 2006: 113-120
53		Pradeep D. Ravikumar, John D. Lafferty: Quadratic programming relaxations for metric labeling and Markov random field MAP estimation. ICML 2006: 737-744
52		Martin J. Wainwright, Pradeep D. Ravikumar, John D. Lafferty: High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression. NIPS 2006: 1465-1472
51		ChengXiang Zhai, John D. Lafferty: A risk minimization framework for information retrieval. Inf. Process. Manage. 42(1): 31-55 (2006)
	2005
50		Xiaojin Zhu, John D. Lafferty: Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning. ICML 2005: 1052-1059
49		David M. Blei, John D. Lafferty: Correlated Topic Models. NIPS 2005
48		Pradeep D. Ravikumar, John D. Lafferty: Preconditioner Approximations for Probabilistic Graphical Models. NIPS 2005
47		John D. Lafferty, Larry A. Wasserman: Rodeo: Sparse Nonparametric Regression in High Dimensions. NIPS 2005
46		John D. Lafferty, Guy Lebanon: Diffusion Kernels on Statistical Manifolds. Journal of Machine Learning Research 6: 129-163 (2005)
	2004
45		Guy Lebanon, John D. Lafferty: Hyperplane margin classifiers on the multinomial manifold. ICML 2004
44		John D. Lafferty, Xiaojin Zhu, Yan Liu: Kernel conditional random fields: representation and clique selection. ICML 2004
43		Avrim Blum, John D. Lafferty, Mugizi Robert Rwebangira, Rajashekar Reddy: Semi-supervised learning using randomized mincuts. ICML 2004
42		Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, John D. Lafferty: Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning. NIPS 2004
41		Pradeep D. Ravikumar, John D. Lafferty: Variational Chernoff Bounds for Graphical Models. UAI 2004: 462-469
40		ChengXiang Zhai, John D. Lafferty: A study of smoothing methods for language models applied to information retrieval. ACM Trans. Inf. Syst. 22(2): 179-214 (2004)
	2003
39		Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty: Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions. ICML 2003: 912-919
38		ChengXiang Zhai, William W. Cohen, John D. Lafferty: Beyond independent relevance: methods and evaluation metrics for subtopic retrieval. SIGIR 2003: 10-17
37		James Allan, Jay Aslam, Nicholas J. Belkin, Chris Buckley, James P. Callan, W. Bruce Croft, Susan T. Dumais, Norbert Fuhr, Donna Harman, David J. Harper, Djoerd Hiemstra, Thomas Hofmann, Eduard H. Hovy, Wessel Kraaij, John D. Lafferty, Victor Lavrenko, David D. Lewis, Liz Liddy, R. Manmatha, Andrew McCallum, Jay M. Ponte, John M. Prager, Dragomir R. Radev, Philip Resnik, Stephen E. Robertson, Ronald Rosenfeld, Salim Roukos, Mark Sanderson, Richard M. Schwartz, Amit Singhal, Alan F. Smeaton, Howard R. Turtle, Ellen M. Voorhees, Ralph M. Weischedel, Jinxi Xu, ChengXiang Zhai: Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002. SIGIR Forum 37(1): 31-47 (2003)
	2002
36		Shyjan Mahamud, Martial Hebert, John D. Lafferty: Combining Simple Discriminators for Object Discrimination. ECCV (3) 2002: 776-790
35		Risi Imre Kondor, John D. Lafferty: Diffusion Kernels on Graphs and Other Discrete Input Spaces. ICML 2002: 315-322
34		Guy Lebanon, John D. Lafferty: Cranking: Combining Rankings Using Conditional Probability Models on Permutations. ICML 2002: 363-370
33		John D. Lafferty, Guy Lebanon: Information Diffusion Kernels. NIPS 2002: 375-382
32		Guy Lebanon, John D. Lafferty: Conditional Models on the Ranking Poset. NIPS 2002: 415-422
31		ChengXiang Zhai, John D. Lafferty: Two-stage language models for information retrieval. SIGIR 2002: 49-56
30		Thomas P. Minka, John D. Lafferty: Expectation-Propogation for the Generative Aspect Model. UAI 2002: 352-359
	2001
29		ChengXiang Zhai, John D. Lafferty: Model-based Feedback in the Language Modeling Approach to Information Retrieval. CIKM 2001: 403-410
28		John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. ICML 2001: 282-289
27		Guy Lebanon, John D. Lafferty: Boosting and Maximum Likelihood for Exponential Models. NIPS 2001: 447-454
26		John D. Lafferty, ChengXiang Zhai: Document Language Models, Query Models, and Risk Minimization for Information Retrieval. SIGIR 2001: 111-119
25		ChengXiang Zhai, John D. Lafferty: A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval. SIGIR 2001: 334-342
24		John D. Lafferty, Larry A. Wasserman: Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk. UAI 2001: 293-300
23		W. Bruce Croft, James P. Callan, John D. Lafferty: Workshop on language modeling and information retrieval. SIGIR Forum 35(1): 4-6 (2001)
	1999
22		John D. Lafferty: Additive Models, Boosting, and Inference for Generalized Divergences. COLT 1999: 125-133
21		Adam L. Berger, John D. Lafferty: Information Retrieval as Statistical Translation. SIGIR 1999: 222-229
20		Adam L. Berger, John D. Lafferty: The Weaver System for Document Retrieval. TREC 1999
19		John D. Lafferty, Alexander Vardy: Ordered Binary Decision Diagrams and Minimal Trellises. IEEE Trans. Computers 48(9): 971-987 (1999)
18		Doug Beeferman, Adam L. Berger, John D. Lafferty: Statistical Models for Text Segmentation. Machine Learning 34(1-3): 177-210 (1999)
	1997
17		Doug Beeferman, Adam L. Berger, John D. Lafferty: A Model of Lexical Attraction and Repulsion. ACL 1997: 373-380
16		John D. Lafferty, Daniel N. Rockmore: Spectral Techniques for Expander Codes. STOC 1997: 160-167
15		Doug Beeferman, Adam L. Berger, John D. Lafferty: Text Segmentation Using Exponential Models CoRR cmp-lg/9706016: (1997)
14		Doug Beeferman, Adam L. Berger, John D. Lafferty: A Model of Lexical Attraction and Repulsion CoRR cmp-lg/9706018: (1997)
13		Stephen Della Pietra, Vincent J. Della Pietra, John D. Lafferty: Inducing Features of Random Fields. IEEE Trans. Pattern Anal. Mach. Intell. 19(4): 380-393 (1997)
	1996
12		Paul Placeway, John D. Lafferty: Cheating with imperfect transcripts. ICSLP 1996
11		Ye-Yi Wang, John D. Lafferty, Alex Waibel: Word clustering with parallel spoken language corpora. ICSLP 1996
	1995
10		Stephen Della Pietra, Vincent J. Della Pietra, John D. Lafferty: Inducing Features of Random Fields CoRR abs/cmp-lg/9506014: (1995)
9		Dennis Grinberg, John D. Lafferty, Daniel Dominic Sleator: A Robust Parsing Algorithm For Link Grammars CoRR abs/cmp-lg/9508003: (1995)
8		John D. Lafferty, Bernhard Suhm: Cluster Expansions and Iterative Scaling for Maximum Entropy Language Models CoRR abs/cmp-lg/9509003: (1995)
	1994
7		Frederick Jelinek, John D. Lafferty, David M. Magerman, Robert L. Mercer, Adwait Ratnaparkhi, Salim Roukos: Decision Tree Parsing using a Hidden Derivation Model. HLT 1994
6		Adam L. Berger, Peter F. Brown, Stephen Della Pietra, Vincent J. Della Pietra, John R. Gillett, John D. Lafferty, Robert L. Mercer, Harry Printz, Lubos Ures: The Candide System for Machine Translation. HLT 1994
5		Stephen Della Pietra, Vincent J. Della Pietra, John R. Gillet, John D. Lafferty, Harry Printz, Lubos Ures: Inference and Estimation of a Long-Range Trigram Model. ICGI 1994: 78-92
	1993
4		Ezra Black, Frederick Jelinek, John D. Lafferty, David M. Magerman, Robert L. Mercer, Salim Roukos: Towards History-Based Grammars: Using Richer Models for Probabilistic Parsing. ACL 1993: 31-37
	1992
3		Ezra Black, John D. Lafferty, Salim Roukos: Development and Evaluation of a Broad-Coverage Probabilistic Grammar of English-Language Computer Manuals. ACL 1992: 185-192
	1991
2		Frederick Jelinek, John D. Lafferty: Computation of the Probability of Initial Substring Generation by Stochastic Context-Free Grammars. Computational Linguistics 17(3): 315-323 (1991)
	1990
1		Peter F. Brown, John Cocke, Stephen Della Pietra, Vincent J. Della Pietra, Frederick Jelinek, John D. Lafferty, Robert L. Mercer, Paul S. Roossin: A Statistical Approach to Machine Translation. Computational Linguistics 16(2): 79-85 (1990)

Coauthor Index

1	James Allan	[37]
2	Javed A. Aslam (Jay Aslam)	[37]
3	Doug Beeferman	[14] [15] [17] [18]
4	Nicholas J. Belkin	[37]
5	Yoshua Bengio	[71]
6	Adam L. Berger	[6] [14] [15] [17] [18] [20] [21]
7	Ezra Black	[3] [4]
8	David M. Blei	[49] [54]
9	Avrim Blum	[43]
10	Peter F. Brown	[1] [6]
11	Chris Buckley	[37]
12	James P. Callan (Jamie Callan)	[23] [37]
13	Xi Chen	[73]
14	John Cocke	[1]
15	William W. Cohen	[38] [62]
16	W. Bruce Croft	[23] [37]
17	Aron Culotta	[71] [75]
18	Susan Ditmore	[60]
19	Susan T. Dumais	[37]
20	Norbert Fuhr	[37]
21	Zoubin Ghahramani	[39] [42]
22	John R. Gillet	[5]
23	John R. Gillett	[6]
24	Yihong Gong	[69] [70]
25	Dennis Grinberg	[9]
26	Haijie Gu	[76]
27	Anupam Gupta	[74] [76]
28	Donna Harman	[37]
29	David J. Harper	[37]
30	Martial Hebert	[36]
31	Djoerd Hiemstra	[37]
32	Thomas Hofmann	[37]
33	Eduard H. Hovy	[37]
34	Frederick Jelinek	[1] [2] [4] [7]
35	Jaz S. Kandola	[42]
36	Mladen Kolar	[77]
37	Risi Imre Kondor	[35]
38	Wessel Kraaij	[37]
39	Victor Lavrenko	[37]
40	Guy Lebanon	[27] [32] [33] [34] [45] [46]
41	David D. Lewis	[37]
42	Elizabeth D. Liddy (Liz Liddy)	[37]
43	Yuanqing Lin	[78]
44	Han Liu	[55] [58] [65] [67] [73] [74] [76] [79]
45	Yan Liu	[44]
46	David M. Magerman	[4] [7]
47	Shyjan Mahamud	[36]
48	R. Manmatha (Raghavan Manmatha)	[37]
49	Andrew McCallum	[28] [37]
50	Robert L. Mercer	[1] [4] [6] [7]
51	Thomas P. Minka (Tom Minka)	[30]
52	Ramesh Nallapati	[60] [62]
53	Fernando C. N. Pereira	[28]
54	Stephen Della Pietra	[1] [5] [6] [10] [13]
55	Vincent J. Della Pietra	[1] [5] [6] [10] [13]
56	Paul Placeway	[12]
57	Jay M. Ponte	[37]
58	John M. Prager	[37]
59	Harry Printz	[5] [6]
60	Dragomir R. Radev	[37]
61	Adwait Ratnaparkhi	[7]
62	Pradeep D. Ravikumar	[41] [48] [52] [53] [58]
63	Rajashekar Reddy	[43]
64	Philip Resnik	[37]
65	Stephen E. Robertson (Stephen Robertson)	[37]
66	Daniel N. Rockmore	[16]
67	Paul S. Roossin	[1]
68	Ronald Rosenfeld (Roni Rosenfeld)	[37]
69	Salim Roukos	[3] [4] [7] [37]
70	Mugizi Robert Rwebangira	[43]
71	Mark Sanderson	[37]
72	Dale Schuurmans	[71]
73	Richard M. Schwartz	[37]
74	John Shawe-Taylor	[75]
75	Amit Singhal	[37]
76	Daniel Dominic Sleator	[9]
77	Alan F. Smeaton	[37]
78	Noah A. Smith	[63]
79	Bernhard Suhm	[8]
80	Howard R. Turtle	[37]
81	Kin Ung	[60]
82	Lubos Ures	[5] [6]
83	Douglas L. Vail	[61] [63] [64]
84	Alexander Vardy	[19]
85	Manuela M. Veloso	[61] [64]
86	Ellen M. Voorhees	[37]
87	Alexander H. Waibel (Alex Waibel)	[11]
88	Martin J. Wainwright	[52]
89	Ye-Yi Wang	[11]
90	Larry A. Wasserman	[24] [47] [55] [56] [57] [58] [59] [65] [66] [67] [68] [72] [73] [74] [76] [77] [79]
91	Ralph M. Weischedel	[37]
92	Christopher K. I. Williams	[71] [75]
93	Jinxi Xu	[37]
94	Min Xu	[74] [76]
95	Kai Yu	[69] [70] [78]
96	Richard S. Zemel	[75]
97	ChengXiang Zhai (Chengxiang Zhai)	[25] [26] [29] [31] [37] [38] [40] [51]
98	Shuheng Zhou	[56] [59] [66] [68] [72]
99	Shenghuo Zhu	[69] [70]
100	Xiaojin Zhu (Xiaojin (Jerry) Zhu)	[39] [42] [44] [50]

Colors in the list of coauthors

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