Andrew McCallum

	2012
123		Sebastian Riedel, David A. Smith, Andrew McCallum: Inference by Minimizing Size, Divergence, or their Sum CoRR abs/1203.3511: (2012)
122		Kedar Bellare, Gregory Druck, Andrew McCallum: Alternating Projections for Learning with Expectation Constraints CoRR abs/1205.2660: (2012)
	2011
121		Sameer Singh, Amarnag Subramanya, Fernando C. N. Pereira, Andrew McCallum: Large-Scale Cross-Document Coreference Using Distributed Inference and Hierarchical Models. ACL 2011: 793-803
120		Gregory Druck, Andrew McCallum: Toward interactive training and evaluation. CIKM 2011: 947-956
119		Sebastian Riedel, Andrew McCallum: Fast and Robust Joint Models for Biomedical Event Extraction. EMNLP 2011: 1-12
118		Limin Yao, Aria Haghighi, Sebastian Riedel, Andrew McCallum: Structured Relation Discovery using Generative Models. EMNLP 2011: 1456-1466
117		David M. Mimno, Hanna M. Wallach, Edmund M. Talley, Miriam Leenders, Andrew McCallum: Optimizing Semantic Coherence in Topic Models. EMNLP 2011: 262-272
116		Michael L. Wick, Khashayar Rohanimanesh, Kedar Bellare, Aron Culotta, Andrew McCallum: SampleRank: Training Factor Graphs with Atomic Gradients. ICML 2011: 777-784
115		Michael L. Wick, Andrew McCallum: Query-Aware MCMC. NIPS 2011: 2564-2572
	2010
114		Sebastian Riedel, Limin Yao, Andrew McCallum: Modeling Relations and Their Mentions without Labeled Text. ECML/PKDD (3) 2010: 148-163
113		Limin Yao, Sebastian Riedel, Andrew McCallum: Collective Cross-Document Relation Extraction Without Labelled Data. EMNLP 2010: 1013-1023
112		Sameer Singh, Limin Yao, Sebastian Riedel, Andrew McCallum: Constraint-Driven Rank-Based Learning for Information Extraction. HLT-NAACL 2010: 729-732
111		Gregory Druck, Andrew McCallum: High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models. ICML 2010: 319-326
110		Pallika Kanani, Andrew McCallum, Shaohan Hu: Resource-Bounded Information Extraction: Acquiring Missing Feature Values on Demand. PAKDD (1) 2010: 415-427
109		Sebastian Riedel, David A. Smith, Andrew McCallum: Inference by Minimizing Size, Divergence, or their Sum. UAI 2010: 492-499
108		Michael L. Wick, Andrew McCallum, Gerome Miklau: Scalable Probabilistic Databases with Factor Graphs and MCMC CoRR abs/1005.1934: (2010)
107		Sameer Singh, Michael L. Wick, Andrew McCallum: Distantly Labeling Data for Large Scale Cross-Document Coreference CoRR abs/1005.4298: (2010)
106		Gideon S. Mann, Andrew McCallum: Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data. Journal of Machine Learning Research 11: 955-984 (2010)
105		Michael L. Wick, Andrew McCallum, Gerome Miklau: Scalable Probabilistic Databases with Factor Graphs and MCMC. PVLDB 3(1): 794-804 (2010)
	2009
104		Haizheng Zhang, Myra Spiliopoulou, Bamshad Mobasher, C. Lee Giles, Andrew McCallum, Olfa Nasraoui, Jaideep Srivastava, John Yen: Advances in Web Mining and Web Usage Analysis, 9th International Workshop on Knowledge Discovery on the Web, WebKDD 2007, and 1st International Workshop on Social Networks Analysis, SNA-KDD 2007, San Jose, CA, USA, August 12-15, 2007. Revised Papers Springer 2009
103		Gregory Druck, Gideon S. Mann, Andrew McCallum: Semi-supervised Learning of Dependency Parsers using Generalized Expectation Criteria. ACL/AFNLP 2009: 360-368
102		Sameer Singh, Karl Schultz, Andrew McCallum: Bi-directional Joint Inference for Entity Resolution and Segmentation Using Imperatively-Defined Factor Graphs. ECML/PKDD (2) 2009: 414-429
101		Kedar Bellare, Andrew McCallum: Generalized Expectation Criteria for Bootstrapping Extractors using Record-Text Alignment. EMNLP 2009: 131-140
100		Gregory Druck, Burr Settles, Andrew McCallum: Active Learning by Labeling Features. EMNLP 2009: 81-90
99		David M. Mimno, Hanna M. Wallach, Jason Naradowsky, David A. Smith, Andrew McCallum: Polylingual Topic Models. EMNLP 2009: 880-889
98		Limin Yao, David M. Mimno, Andrew McCallum: Efficient methods for topic model inference on streaming document collections. KDD 2009: 937-946
97		Andrew McCallum, Karl Schultz, Sameer Singh: FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs. NIPS 2009: 1249-1257
96		Hanna M. Wallach, David M. Mimno, Andrew McCallum: Rethinking LDA: Why Priors Matter. NIPS 2009: 1973-1981
95		Michael L. Wick, Khashayar Rohanimanesh, Sameer Singh, Andrew McCallum: Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference. NIPS 2009: 2044-2052
94		Michael L. Wick, Aron Culotta, Khashayar Rohanimanesh, Andrew McCallum: An Entity Based Model for Coreference Resolution. SDM 2009: 365-376
93		Kedar Bellare, Gregory Druck, Andrew McCallum: Alternating Projections for Learning with Expectation Constraints. UAI 2009: 43-50
92		Charles A. Sutton, Andrew McCallum: Piecewise training for structured prediction. Machine Learning 77(2-3): 165-194 (2009)
	2008
91		William W. Cohen, Andrew McCallum, Sam T. Roweis: Machine Learning, Proceedings of the Twenty-Fifth International Conference (ICML 2008), Helsinki, Finland, June 5-9, 2008 ACM 2008
90		Gideon S. Mann, Andrew McCallum: Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields. ACL 2008: 870-878
89		Robert Hall, Charles A. Sutton, Andrew McCallum: Unsupervised deduplication using cross-field dependencies. KDD 2008: 310-317
88		Michael L. Wick, Khashayar Rohanimanesh, Karl Schultz, Andrew McCallum: A unified approach for schema matching, coreference and canonicalization. KDD 2008: 722-730
87		Michael L. Wick, Khashayar Rohanimanesh, Andrew McCallum, AnHai Doan: A Discriminative Approach to Ontology Mapping. NTII 2008: 16-19
86		Gregory Druck, Gideon S. Mann, Andrew McCallum: Learning from labeled features using generalized expectation criteria. SIGIR 2008: 595-602
85		David M. Mimno, Andrew McCallum: Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression. UAI 2008: 411-418
84		Rebecca Reznik-Zellen, Bob Stevens, Michael Thorn, Jeff Morse, Mark D. Smucker, James Allan, David M. Mimno, Andrew McCallum, Mark Tuominen: InterNano: e-Science for the Nanomanufacturing Community. eScience 2008: 382-383
	2007
83		Pallika Kanani, Andrew McCallum: Resource-Bounded Information Gathering for Correlation Clustering. COLT 2007: 625-627
82		Aron Culotta, Michael L. Wick, Andrew McCallum: First-Order Probabilistic Models for Coreference Resolution. HLT-NAACL 2007: 81-88
81		Gideon S. Mann, Andrew McCallum: Efficient Computation of Entropy Gradient for Semi-Supervised Conditional Random Fields. HLT-NAACL (Short Papers) 2007: 109-112
80		Vidit Jain, Erik G. Learned-Miller, Andrew McCallum: People-LDA: Anchoring Topics to People using Face Recognition. ICCV 2007: 1-8
79		Gary B. Huang, Erik G. Learned-Miller, Andrew McCallum: Cryptogram Decoding for OCR Using Numerization Strings. ICDAR 2007: 208-212
78		Xuerui Wang, Andrew McCallum, Xing Wei: Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval. ICDM 2007: 697-702
77		Gideon S. Mann, Andrew McCallum: Simple, robust, scalable semi-supervised learning via expectation regularization. ICML 2007: 593-600
76		David M. Mimno, Wei Li, Andrew McCallum: Mixtures of hierarchical topics with Pachinko allocation. ICML 2007: 633-640
75		Charles A. Sutton, Andrew McCallum: Piecewise pseudolikelihood for efficient training of conditional random fields. ICML 2007: 863-870
74		Pallika Kanani, Andrew McCallum, Chris Pal: Improving Author Coreference by Resource-Bounded Information Gathering from the Web. IJCAI 2007: 429-434
73		David M. Mimno, Andrew McCallum: Mining a digital library for influential authors. JCDL 2007: 105-106
72		David M. Mimno, Andrew McCallum: Organizing the OCA: learning faceted subjects from a library of digital books. JCDL 2007: 376-385
71		Aron Culotta, Michael L. Wick, Robert Hall, Matthew Marzilli, Andrew McCallum: Canonicalization of database records using adaptive similarity measures. KDD 2007: 201-209
70		Gregory Druck, Chris Pal, Andrew McCallum, Xiaojin Zhu: Semi-supervised classification with hybrid generative/discriminative methods. KDD 2007: 280-289
69		David M. Mimno, Andrew McCallum: Expertise modeling for matching papers with reviewers. KDD 2007: 500-509
68		Xuerui Wang, Chris Pal, Andrew McCallum: Generalized component analysis for text with heterogeneous attributes. KDD 2007: 794-803
67		Wei Li, David M. Blei, Andrew McCallum: Nonparametric Bayes Pachinko Allocation. UAI 2007: 243-250
66		Charles A. Sutton, Andrew McCallum: Improved Dynamic Schedules for Belief Propagation. UAI 2007: 376-383
65		Andrew McCallum, Xuerui Wang, Andrés Corrada-Emmanuel: Topic and Role Discovery in Social Networks with Experiments on Enron and Academic Email. J. Artif. Intell. Res. (JAIR) 30: 249-272 (2007)
64		Charles A. Sutton, Andrew McCallum, Khashayar Rohanimanesh: Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data. Journal of Machine Learning Research 8: 693-723 (2007)
63		Haizheng Zhang, John Yen, C. Lee Giles, Bamshad Mobasher, Myra Spiliopoulou, Jaideep Srivastava, Olfa Nasraoui, Andrew McCallum: WebKDD/SNAKDD 2007: web mining and social network analysis post-workshop report. SIGKDD Explorations 9(2): 87-92 (2007)
	2006
62		Andrew McCallum, Chris Pal, Gregory Druck, Xuerui Wang: Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification. AAAI 2006: 433-439
61		Shaolei Feng, R. Manmatha, Andrew McCallum: Exploring the Use of Conditional Random Field Models and HMMs for Historical Handwritten Document Recognition. DIAL 2006: 30-37
60		Michael L. Wick, Aron Culotta, Andrew McCallum: Learning Field Compatibilities to Extract Database Records from Unstructured Text. EMNLP 2006: 603-611
59		Aron Culotta, Andrew McCallum, Jonathan Betz: Integrating Probabilistic Extraction Models and Data Mining to Discover Relations and Patterns in Text. HLT-NAACL 2006
58		Charles A. Sutton, Michael Sindelar, Andrew McCallum: Reducing Weight Undertraining in Structured Discriminative Learning. HLT-NAACL 2006
57		Wei Li, Andrew McCallum: Pachinko allocation: DAG-structured mixture models of topic correlations. ICML 2006: 577-584
56		B. Michael Kelm, Chris Pal, Andrew McCallum: Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning. ICPR (2) 2006: 828-832
55		Gideon S. Mann, David M. Mimno, Andrew McCallum: Bibliometric impact measures leveraging topic analysis. JCDL 2006: 65-74
54		Xuerui Wang, Andrew McCallum: Topics over time: a non-Markov continuous-time model of topical trends. KDD 2006: 424-433
53		Andrew McCallum: Information extraction, data mining and joint inference. KDD 2006: 835
52		Aron Culotta, Trausti T. Kristjansson, Andrew McCallum, Paul A. Viola: Corrective feedback and persistent learning for information extraction. Artif. Intell. 170(14-15): 1101-1122 (2006)
51		Fuchun Peng, Andrew McCallum: Information extraction from research papers using conditional random fields. Inf. Process. Manage. 42(4): 963-979 (2006)
50		Xing Wei, W. Bruce Croft, Andrew McCallum: Table extraction for answer retrieval. Inf. Retr. 9(5): 589-611 (2006)
	2005
49		Aron Culotta, Andrew McCallum: Reducing Labeling Effort for Structured Prediction Tasks. AAAI 2005: 746-751
48		Wei Li, Andrew McCallum: Semi-Supervised Sequence Modeling with Syntactic Topic Models. AAAI 2005: 813-818
47		Nadia Ghamrawi, Andrew McCallum: Collective multi-label classification. CIKM 2005: 195-200
46		Aron Culotta, Andrew McCallum: Joint deduplication of multiple record types in relational data. CIKM 2005: 257-258
45		Charles A. Sutton, Andrew McCallum: Composition of Conditional Random Fields for Transfer Learning. HLT/EMNLP 2005
44		Ron Bekkerman, Ran El-Yaniv, Andrew McCallum: Multi-way distributional clustering via pairwise interactions. ICML 2005: 41-48
43		Andrew McCallum, Andrés Corrada-Emmanuel, Xuerui Wang: Topic and Role Discovery in Social Networks. IJCAI 2005: 786-791
42		Yu Gu, Andrew McCallum, Donald F. Towsley: Detecting Anomalies in Network Traffic Using Maximum Entropy Estimation. Internet Measurment Conference 2005: 345-350
41		Xuerui Wang, Natasha Mohanty, Andrew McCallum: Group and Topic Discovery from Relations and Their Attributes. NIPS 2005
40		Andrew McCallum, Kedar Bellare, Fernando C. N. Pereira: A Conditional Random Field for Discriminatively-trained Finite-state String Edit Distance. UAI 2005: 388-395
39		Charles A. Sutton, Andrew McCallum: Piecewise Training for Undirected Models. UAI 2005: 568-575
38		Ron Bekkerman, Andrew McCallum: Disambiguating Web appearances of people in a social network. WWW 2005: 463-470
37		Andrew McCallum: Information extraction: distilling structured data from unstructured text. ACM Queue 3(9): 48-57 (2005)
	2004
36		Trausti T. Kristjansson, Aron Culotta, Paul A. Viola, Andrew McCallum: Interactive Information Extraction with Constrained Conditional Random Fields. AAAI 2004: 412-418
35		Aron Culotta, Ron Bekkerman, Andrew McCallum: Extracting social networks and contact information from email and the Web. CEAS 2004
34		Fuchun Peng, Andrew McCallum: Accurate Information Extraction from Research Papers using Conditional Random Fields. HLT-NAACL 2004: 329-336
33		Charles A. Sutton, Khashayar Rohanimanesh, Andrew McCallum: Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data. ICML 2004
32		Andrew McCallum, Ben Wellner: Conditional Models of Identity Uncertainty with Application to Noun Coreference. NIPS 2004
31		Ben Wellner, Andrew McCallum, Fuchun Peng, Michael Hay: An Integrated, Conditional Model of Information Extraction and Coreference with Appli. UAI 2004: 593-601
	2003
30		David Pinto, Andrew McCallum, Xing Wei, W. Bruce Croft: Table Extraction Using Conditional Random Fields. DG.O 2003
29		Andrew McCallum, Ben Wellner: Toward Conditional Models of Identity Uncertainty with Application to Proper Noun Coreference. IIWeb 2003: 79-84
28		Rajat Raina, Yirong Shen, Andrew Y. Ng, Andrew McCallum: Classification with Hybrid Generative/Discriminative Models. NIPS 2003
27		David Pinto, Andrew McCallum, Xing Wei, W. Bruce Croft: Table extraction using conditional random fields. SIGIR 2003: 235-242
26		Andrew McCallum: Efficiently Inducing Features of Conditional Random Fields. UAI 2003: 403-410
25		Wei Li, Andrew McCallum: Rapid development of Hindi named entity recognition using conditional random fields and feature induction. ACM Trans. Asian Lang. Inf. Process. 2(3): 290-294 (2003)
24		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
23		David M. Blei, J. Andrew Bagnell, Andrew McCallum: Learning with Scope, with Application to Information Extraction and Classification. UAI 2002: 53-60
	2001
22		John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. ICML 2001: 282-289
21		Nicholas Roy, Andrew McCallum: Toward Optimal Active Learning through Sampling Estimation of Error Reduction. ICML 2001: 441-448
	2000
20		Dayne Freitag, Andrew McCallum: Information Extraction with HMM Structures Learned by Stochastic Optimization. AAAI/IAAI 2000: 584-589
19		Huan Chang, David Cohn, Andrew McCallum: Learning to Create Customized Authority Lists. ICML 2000: 127-134
18		Andrew McCallum, Dayne Freitag, Fernando C. N. Pereira: Maximum Entropy Markov Models for Information Extraction and Segmentation. ICML 2000: 591-598
17		Andrew McCallum, Kamal Nigam, Lyle H. Ungar: Efficient clustering of high-dimensional data sets with application to reference matching. KDD 2000: 169-178
16		Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery: Learning to construct knowledge bases from the World Wide Web. Artif. Intell. 118(1-2): 69-113 (2000)
15		William W. Cohen, Andrew McCallum, Dallan Quass: Learning to Understand the Web. IEEE Data Eng. Bull. 23(3): 17-24 (2000)
14		Andrew McCallum, Kamal Nigam, Jason Rennie, Kristie Seymore: Automating the Construction of Internet Portals with Machine Learning. Inf. Retr. 3(2): 127-163 (2000)
13		Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell: Text Classification from Labeled and Unlabeled Documents using EM. Machine Learning 39(2/3): 103-134 (2000)
	1999
12		Jason Rennie, Andrew McCallum: Using Reinforcement Learning to Spider the Web Efficiently. ICML 1999: 335-343
11		Andrew McCallum, Kamal Nigam, Jason Rennie, Kristie Seymore: A Machine Learning Approach to Building Domain-Specific Search Engines. IJCAI 1999: 662-667
	1998
10		Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery: Learning to Extract Symbolic Knowledge from the World Wide Web. AAAI/IAAI 1998: 509-516
9		Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell: Learning to Classify Text from Labeled and Unlabeled Documents. AAAI/IAAI 1998: 792-799
8		Andrew McCallum, Kamal Nigam: Employing EM and Pool-Based Active Learning for Text Classification. ICML 1998: 350-358
7		Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng: Improving Text Classification by Shrinkage in a Hierarchy of Classes. ICML 1998: 359-367
6		L. Douglas Baker, Andrew McCallum: Distributional Clustering of Words for Text Classification. SIGIR 1998: 96-103
	1995
5		Andrew McCallum: Instance-Based Utile Distinctions for Reinforcement Learning with Hidden State. ICML 1995: 387-395
	1994
4		Andrew McCallum: Instance-Based State Identification for Reinforcement Learning. NIPS 1994: 377-384
	1993
3		Andrew McCallum: Overcoming Incomplete Perception with Util Distinction Memory. ICML 1993: 190-196
	1992
2		Andrew McCallum: Using Transitional Proximity for Faster Reinforcement Learning. ML 1992: 316-321
	1990
1		Andrew McCallum, Kent A. Spackman: Using Genetic Algorithms to Learn Disjunctive Rules from Examples. ML 1990: 149-152

Coauthor Index

1	James Allan	[24] [84]
2	Javed A. Aslam (Jay Aslam)	[24]
3	J. Andrew Bagnell (Drew Bagnell)	[23]
4	L. Douglas Baker	[6]
5	Ron Bekkerman	[35] [38] [44]
6	Nicholas J. Belkin	[24]
7	Kedar Bellare	[40] [93] [101] [116] [122]
8	Jonathan Betz	[59]
9	David M. Blei	[23] [67]
10	Chris Buckley	[24]
11	James P. Callan (Jamie Callan)	[24]
12	Huan Chang	[19]
13	William W. Cohen	[15] [91]
14	David Cohn	[19]
15	Andrés Corrada-Emmanuel (Andrés Corrada)	[43] [65]
16	Mark Craven	[10] [16]
17	W. Bruce Croft	[24] [27] [30] [50]
18	Aron Culotta	[35] [36] [46] [49] [52] [59] [60] [71] [82] [94] [116]
19	Dan DiPasquo	[10] [16]
20	AnHai Doan	[87]
21	Gregory Druck	[62] [70] [86] [93] [100] [103] [111] [120] [122]
22	Susan T. Dumais	[24]
23	Ran El-Yaniv	[44]
24	Shaolei Feng	[61]
25	Dayne Freitag	[10] [16] [18] [20]
26	Norbert Fuhr	[24]
27	Nadia Ghamrawi	[47]
28	C. Lee Giles (Clyde Lee Giles)	[63] [104]
29	Yu Gu	[42]
30	Aria Haghighi	[118]
31	Robert Hall	[71] [89]
32	Donna Harman	[24]
33	David J. Harper	[24]
34	Michael Hay	[31]
35	Djoerd Hiemstra	[24]
36	Thomas Hofmann	[24]
37	Eduard H. Hovy	[24]
38	Shaohan Hu	[110]
39	Gary B. Huang	[79]
40	Vidit Jain	[80]
41	Pallika Kanani	[74] [83] [110]
42	B. Michael Kelm	[56]
43	Wessel Kraaij	[24]
44	Trausti T. Kristjansson	[36] [52]
45	John D. Lafferty	[22] [24]
46	Victor Lavrenko	[24]
47	Erik G. Learned-Miller	[79] [80]
48	Miriam Leenders	[117]
49	David D. Lewis	[24]
50	Wei Li	[67]
51	Wei Li	[25] [48] [57] [76]
52	Elizabeth D. Liddy (Liz Liddy)	[24]
53	R. Manmatha (Raghavan Manmatha)	[24] [61]
54	Gideon S. Mann	[55] [77] [81] [86] [90] [103] [106]
55	Matthew Marzilli	[71]
56	Gerome Miklau	[105] [108]
57	David M. Mimno	[55] [69] [72] [73] [76] [84] [85] [96] [98] [99] [117]
58	Tom M. Mitchell	[7] [9] [10] [13] [16]
59	Bamshad Mobasher	[63] [104]
60	Natasha Mohanty	[41]
61	Jeff Morse	[84]
62	Jason Naradowsky	[99]
63	Olfa Nasraoui	[63] [104]
64	Andrew Y. Ng	[7] [28]
65	Kamal Nigam	[8] [9] [10] [11] [13] [14] [16] [17]
66	Christopher J. Pal (Chris Pal)	[56] [62] [68] [70] [74]
67	Fuchun Peng	[31] [34] [51]
68	Fernando C. N. Pereira	[18] [22] [40] [121]
69	David Pinto (David Pinto Avendaño, David Eduardo Pinto)	[27] [30]
70	Jay M. Ponte	[24]
71	John M. Prager	[24]
72	Dallan Quass	[15]
73	Dragomir R. Radev	[24]
74	Rajat Raina	[28]
75	Jason Rennie	[11] [12] [14]
76	Philip Resnik	[24]
77	Rebecca Reznik-Zellen	[84]
78	Sebastian Riedel	[109] [112] [113] [114] [118] [119] [123]
79	Stephen E. Robertson (Stephen Robertson)	[24]
80	Khashayar Rohanimanesh	[33] [64] [87] [88] [94] [95] [116]
81	Ronald Rosenfeld (Roni Rosenfeld)	[7] [24]
82	Salim Roukos	[24]
83	Sam T. Roweis	[91]
84	Nicholas Roy	[21]
85	Mark Sanderson	[24]
86	Karl Schultz	[88] [97] [102]
87	Richard M. Schwartz	[24]
88	Burr Settles	[100]
89	Kristie Seymore	[11] [14]
90	Yirong Shen	[28]
91	Michael Sindelar	[58]
92	Sameer Singh	[95] [97] [102] [107] [112] [121]
93	Amit Singhal	[24]
94	Seán Slattery	[10] [16]
95	Alan F. Smeaton	[24]
96	David A. Smith	[99] [109] [123]
97	Mark D. Smucker	[84]
98	Kent A. Spackman	[1]
99	Myra Spiliopoulou	[63] [104]
100	Jaideep Srivastava	[63] [104]
101	Bob Stevens	[84]
102	Amarnag Subramanya (Amar Subramanya)	[121]
103	Charles A. Sutton	[33] [39] [45] [58] [64] [66] [75] [89] [92]
104	Edmund M. Talley	[117]
105	Michael Thorn	[84]
106	Sebastian Thrun	[9] [13]
107	Donald F. Towsley (Don Towsley)	[42]
108	Mark Tuominen	[84]
109	Howard R. Turtle	[24]
110	Lyle H. Ungar	[17]
111	Paul A. Viola	[36] [52]
112	Ellen M. Voorhees	[24]
113	Hanna M. Wallach	[96] [99] [117]
114	Xuerui Wang	[41] [43] [54] [62] [65] [68] [78]
115	Xing Wei	[27] [30] [50] [78]
116	Ralph M. Weischedel	[24]
117	Ben Wellner (Benjamin Wellner)	[29] [31] [32]
118	Michael L. Wick	[60] [71] [82] [87] [88] [94] [95] [105] [107] [108] [115] [116]
119	Jinxi Xu	[24]
120	Limin Yao	[98] [112] [113] [114] [118]
121	John Yen	[63] [104]
122	ChengXiang Zhai (Chengxiang Zhai)	[24]
123	Haizheng Zhang	[63] [104]
124	Xiaojin Zhu (Xiaojin (Jerry) Zhu)	[70]

Colors in the list of coauthors

Last update Mon Jun 4 20:40:43 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page