Pedro Domingos

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2007

88 Hoifung Poon, Pedro Domingos: Joint Inference in Information Extraction. AAAI 2007: 913-918

87 EE Stanley Kok, Pedro Domingos: Statistical predicate invention. ICML 2007: 433-440

86 EE Daniel Lowd, Pedro Domingos: Recursive Random Fields. IJCAI 2007: 950-955

85 EE Daniel Lowd, Pedro Domingos: Efficient Weight Learning for Markov Logic Networks. PKDD 2007: 200-211

84 EE Pedro Domingos: Toward knowledge-rich data mining. Data Min. Knowl. Discov. 15(1): 21-28 (2007)

2006

83 Parag Singla, Pedro Domingos: Memory-Efficient Inference in Relational Domains. AAAI 2006

82 Hoifung Poon, Pedro Domingos: Sound and Efficient Inference with Probabilistic and Deterministic Dependencies. AAAI 2006

81 Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla: Unifying Logical and Statistical AI. AAAI 2006

80 EE Pedro Domingos: Learning, Logic, and Probability: A Unified View. EKAW 2006: 2

79 EE Pedro Domingos: Learning, Logic, and Probability: A Unified View. IBERAMIA-SBIA 2006: 3

78 EE Parag Singla, Pedro Domingos: Entity Resolution with Markov Logic. ICDM 2006: 572-582

77 EE Pedro Domingos: Learning, Logic, and Probability: A Unified View. PRICAI 2006: 1

76 EE Matthew Richardson, Pedro Domingos: Markov logic networks. Machine Learning 62(1-2): 107-136 (2006)

2005

75 Parag Singla, Pedro Domingos: Discriminative Training of Markov Logic Networks. AAAI 2005: 868-873

74 Pedro Domingos, Fernando M. Silva, Horácio C. Neto: An Efficient and Scalable Architecture for Neural Networks with Backpropagation Learning. FPL 2005: 89-94

73 EE Stanley Kok, Pedro Domingos: Learning the structure of Markov logic networks. ICML 2005: 441-448

72 EE Daniel Lowd, Pedro Domingos: Naive Bayes models for probability estimation. ICML 2005: 529-536

71 EE Parag Singla, Pedro Domingos: Collective Object Identification. IJCAI 2005: 1636-1637

70 EE Parag Singla, Pedro Domingos: Object Identification with Attribute-Mediated Dependences. PKDD 2005: 297-308

69 Michael L. Anderson, Thomas Barkowsky, Pauline Berry, Douglas S. Blank, Timothy Chklovski, Pedro Domingos, Marek J. Druzdzel, Christian Freksa, John Gersh, Mary Hegarty, Tze-Yun Leong, Henry Lieberman, Ric K. Lowe, Susann Luperfoy, Rada Mihalcea, Lisa Meeden, David P. Miller, Tim Oates, Robert Popp, Daniel Shapiro, Nathan Schurr, Push Singh, John Yen: Reports on the 2005 AAAI Spring Symposium Series. AI Magazine 26(2): 87-92 (2005)

68 EE Steffen Staab, Pedro Domingos, Peter Mika, Jennifer Golbeck, Li Ding, Timothy W. Finin, Anupam Joshi, Andrzej Nowak, Robin R. Vallacher: Social Networks Applied. IEEE Intelligent Systems 20(1): 80-93 (2005)

67 EE Sumit K. Sanghai, Pedro Domingos, Daniel S. Weld: Relational Dynamic Bayesian Networks. J. Artif. Intell. Res. (JAIR) 24: 759-797 (2005)

2004

66 EE Pedro Domingos: Learning, Logic, and Probability: A Unified View. ALT 2004: 53

65 EE Pedro Domingos: Real-World Learning with Markov Logic Networks. ECML 2004: 17

64 EE Daniel Grossman, Pedro Domingos: Learning Bayesian network classifiers by maximizing conditional likelihood. ICML 2004

63 EE Pedro Domingos: Learning, Logic, and Probability: A Unified View. ILP 2004: 359

62 EE Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. Sanghai, Deepak Verma: Adversarial classification. KDD 2004: 99-108

61 EE Pedro Domingos: Real-World Learning with Markov Logic Networks. PKDD 2004: 17

60 EE Robin Dhamankar, Yoonkyong Lee, AnHai Doan, Alon Y. Halevy, Pedro Domingos: iMAP: Discovering Complex Mappings between Database Schemas. SIGMOD Conference 2004: 383-394

59 AnHai Doan, Jayant Madhavan, Pedro Domingos, Alon Y. Halevy: Ontology Matching: A Machine Learning Approach. Handbook on Ontologies 2004: 385-404

58 Matthew Richardson, Pedro Domingos: Combining Link and Content Information in Web Search. Web Dynamics 2004: 179-194

2003

57 Lise Getoor, Ted E. Senator, Pedro Domingos, Christos Faloutsos: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24 - 27, 2003 ACM 2003

56 EE Pedro Domingos, Matt Richardson: Learning from Networks of Examples. EPIA 2003: 5

55 Matt Richardson, Pedro Domingos: Learning with Knowledge from Multiple Experts. ICML 2003: 624-631

54 Daniel S. Weld, Corin R. Anderson, Pedro Domingos, Oren Etzioni, Krzysztof Gajos, Tessa A. Lau, Steven A. Wolfman: Automatically Personalizing User Interfaces. IJCAI 2003: 1613-1619

53 EE Matthew Richardson, Rakesh Agrawal, Pedro Domingos: Trust Management for the Semantic Web. International Semantic Web Conference 2003: 351-368

52 EE Matthew Richardson, Pedro Domingos: Building large knowledge bases by mass collaboration. K-CAP 2003: 129-137

51 EE Tessa A. Lau, Pedro Domingos, Daniel S. Weld: Learning programs from traces using version space algebra. K-CAP 2003: 36-43

50 AnHai Doan, Pedro Domingos, Alon Y. Halevy: Learning to Match the Schemas of Data Sources: A Multistrategy Approach. Machine Learning 50(3): 279-301 (2003)

49 EE Foster J. Provost, Pedro Domingos: Tree Induction for Probability-Based Ranking. Machine Learning 52(3): 199-215 (2003)

48 EE Tessa A. Lau, Steven A. Wolfman, Pedro Domingos, Daniel S. Weld: Programming by Demonstration Using Version Space Algebra. Machine Learning 53(1-2): 111-156 (2003)

47 EE Pedro Domingos: Prospects and challenges for multi-relational data mining. SIGKDD Explorations 5(1): 80-83 (2003)

46 EE AnHai Doan, Jayant Madhavan, Robin Dhamankar, Pedro Domingos, Alon Y. Halevy: Learning to match ontologies on the Semantic Web. VLDB J. 12(4): 303-319 (2003)

2002

45 Jayant Madhavan, Philip A. Bernstein, Pedro Domingos, Alon Y. Halevy: Representing and Reasoning about Mappings between Domain Models. AAAI/IAAI 2002: 80-86

44 EE Corin R. Anderson, Pedro Domingos, Daniel S. Weld: Relational Markov models and their application to adaptive web navigation. KDD 2002: 143-152

43 EE Geoff Hulten, Pedro Domingos: Mining complex models from arbitrarily large databases in constant time. KDD 2002: 525-531

42 EE Matt Richardson, Pedro Domingos: Mining knowledge-sharing sites for viral marketing. KDD 2002: 61-70

41 EE AnHai Doan, Jayant Madhavan, Pedro Domingos, Alon Y. Halevy: Learning to map between ontologies on the semantic web. WWW 2002: 662-673

40 EE Pedro Domingos: When and How to Subsample: Report on the KDD-2001 Panel. SIGKDD Explorations 3(2): 74-75 (2002)

2001

39 EE Pedro Domingos, Geoff Hulten: Catching up with the Data: Research Issues in Mining Data Streams. DMKD 2001

38 Pedro Domingos, Geoff Hulten: A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering. ICML 2001: 106-113

37 Corin R. Anderson, Pedro Domingos, Daniel S. Weld: Adaptive Web Navigation for Wireless Devices. IJCAI 2001: 879-884

36 EE Steven A. Wolfman, Tessa A. Lau, Pedro Domingos, Daniel S. Weld: Mixed initiative interfaces for learning tasks: SMARTedit talks back. Intelligent User Interfaces 2001: 167-174

35 EE Pedro Domingos, Matt Richardson: Mining the network value of customers. KDD 2001: 57-66

34 EE Geoff Hulten, Laurie Spencer, Pedro Domingos: Mining time-changing data streams. KDD 2001: 97-106

33 EE Matt Richardson, Pedro Domingos: The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank. NIPS 2001: 1441-1448

32 EE Pedro Domingos, Geoff Hulten: Learning from Infinite Data in Finite Time. NIPS 2001: 673-680

31 EE AnHai Doan, Pedro Domingos, Alon Y. Halevy: Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach. SIGMOD Conference 2001: 509-520

30 EE Corin R. Anderson, Pedro Domingos, Daniel S. Weld: Personalizing Web Sites for Mobile Users. WWW 2001: 565-575

2000

29 Pedro Domingos: A Unified Bias-Variance Decomposition for Zero-One and Squared Loss. AAAI/IAAI 2000: 564-569

28 EE Pedro Domingos: Beyond Occam's Razor: Process-Oriented Evaluation. ECML 2000: 3

27 Pedro Domingos: Bayesian Averaging of Classifiers and the Overfitting Problem. ICML 2000: 223-230

26 Pedro Domingos: A Unifeid Bias-Variance Decomposition and its Applications. ICML 2000: 231-238

25 Tessa A. Lau, Pedro Domingos, Daniel S. Weld: Version Space Algebra and its Application to Programming by Demonstration. ICML 2000: 527-534

24 EE Pedro Domingos, Geoff Hulten: Mining high-speed data streams. KDD 2000: 71-80

23 EE AnHai Doan, Pedro Domingos, Alon Y. Levy: Learning Source Description for Data Integration. WebDB (Informal Proceedings) 2000: 81-86

1999

22 Pedro Domingos: Process-Oriented Estimation of Generalization Error. IJCAI 1999: 714-721

21 EE Pedro Domingos: MetaCost: A General Method for Making Classifiers Cost-Sensitive. KDD 1999: 155-164

20 Pedro Domingos: The Role of Occam's Razor in Knowledge Discovery. Data Min. Knowl. Discov. 3(4): 409-425 (1999)

1998

19 Pedro Domingos: A Process-Oriented Heuristic for Model Selection. ICML 1998: 127-135

18 Pedro Domingos: Occam's Two Razors: The Sharp and the Blunt. KDD 1998: 37-43

17 EE Pedro Domingos: Knowledge Discovery Via Multiple Models. Intell. Data Anal. 2(1-4): 187-202 (1998)

1997

16 Pedro Domingos: A Comparison of Model Averaging Methods in Foreign Exchange Prediction. AAAI/IAAI 1997: 828

15 Pedro Domingos: Learning Multiple Models without Sacrificing Comprehensibility. AAAI/IAAI 1997: 829

14 Pedro Domingos: Knowledge Acquisition form Examples Vis Multiple Models. ICML 1997: 98-106

13 Pedro Domingos: Why Does Bagging Work? A Bayesian Account and its Implications. KDD 1997: 155-158

12 Pedro Domingos: Control-Sensitive Feature Selection for Lazy Learners. Artif. Intell. Rev. 11(1-5): 227-253 (1997)

11 Pedro Domingos, Michael J. Pazzani: On the Optimality of the Simple Bayesian Classifier under Zero-One Loss. Machine Learning 29(2-3): 103-130 (1997)

1996

10 Pedro Domingos: Towards a Unified Approach to Concept Learning. AAAI/IAAI, Vol. 2 1996: 1361

9 Pedro Domingos: Fast Discovery of Simple Rules. AAAI/IAAI, Vol. 2 1996: 1384

8 Pedro Domingos: Multistrategy Learning: A Case Study. AAAI/IAAI, Vol. 2 1996: 1385

7 Pedro Domingos, Michael J. Pazzani: Simple Bayesian Classifiers Do Not Assume Independence. AAAI/IAAI, Vol. 2 1996: 1386

6 Pedro Domingos, Michael J. Pazzani: Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier. ICML 1996: 105-112

5 Pedro Domingos: Efficient Specific-to-General Rule Induction. KDD 1996: 319-322

4 Pedro Domingos: Linear-Time Rule Induction. KDD 1996: 96-101

3 Pedro Domingos: Unifying Instance-Based and Rule-Based Induction. Machine Learning 24(2): 141-168 (1996)

1995

2 Pedro Domingos: Rule Induction and Instance-Based Learning: A Unified Approach. IJCAI 1995: 1226-1232

1994

1 Pedro Domingos: The RISE System: Conquering without Separating. ICTAI 1994: 704-707

2007
88		Hoifung Poon, Pedro Domingos: Joint Inference in Information Extraction. AAAI 2007: 913-918
87	EE	Stanley Kok, Pedro Domingos: Statistical predicate invention. ICML 2007: 433-440
86	EE	Daniel Lowd, Pedro Domingos: Recursive Random Fields. IJCAI 2007: 950-955
85	EE	Daniel Lowd, Pedro Domingos: Efficient Weight Learning for Markov Logic Networks. PKDD 2007: 200-211
84	EE	Pedro Domingos: Toward knowledge-rich data mining. Data Min. Knowl. Discov. 15(1): 21-28 (2007)
2006
83		Parag Singla, Pedro Domingos: Memory-Efficient Inference in Relational Domains. AAAI 2006
82		Hoifung Poon, Pedro Domingos: Sound and Efficient Inference with Probabilistic and Deterministic Dependencies. AAAI 2006
81		Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla: Unifying Logical and Statistical AI. AAAI 2006
80	EE	Pedro Domingos: Learning, Logic, and Probability: A Unified View. EKAW 2006: 2
79	EE	Pedro Domingos: Learning, Logic, and Probability: A Unified View. IBERAMIA-SBIA 2006: 3
78	EE	Parag Singla, Pedro Domingos: Entity Resolution with Markov Logic. ICDM 2006: 572-582
77	EE	Pedro Domingos: Learning, Logic, and Probability: A Unified View. PRICAI 2006: 1
76	EE	Matthew Richardson, Pedro Domingos: Markov logic networks. Machine Learning 62(1-2): 107-136 (2006)
2005
75		Parag Singla, Pedro Domingos: Discriminative Training of Markov Logic Networks. AAAI 2005: 868-873
74		Pedro Domingos, Fernando M. Silva, Horácio C. Neto: An Efficient and Scalable Architecture for Neural Networks with Backpropagation Learning. FPL 2005: 89-94
73	EE	Stanley Kok, Pedro Domingos: Learning the structure of Markov logic networks. ICML 2005: 441-448
72	EE	Daniel Lowd, Pedro Domingos: Naive Bayes models for probability estimation. ICML 2005: 529-536
71	EE	Parag Singla, Pedro Domingos: Collective Object Identification. IJCAI 2005: 1636-1637
70	EE	Parag Singla, Pedro Domingos: Object Identification with Attribute-Mediated Dependences. PKDD 2005: 297-308
69		Michael L. Anderson, Thomas Barkowsky, Pauline Berry, Douglas S. Blank, Timothy Chklovski, Pedro Domingos, Marek J. Druzdzel, Christian Freksa, John Gersh, Mary Hegarty, Tze-Yun Leong, Henry Lieberman, Ric K. Lowe, Susann Luperfoy, Rada Mihalcea, Lisa Meeden, David P. Miller, Tim Oates, Robert Popp, Daniel Shapiro, Nathan Schurr, Push Singh, John Yen: Reports on the 2005 AAAI Spring Symposium Series. AI Magazine 26(2): 87-92 (2005)
68	EE	Steffen Staab, Pedro Domingos, Peter Mika, Jennifer Golbeck, Li Ding, Timothy W. Finin, Anupam Joshi, Andrzej Nowak, Robin R. Vallacher: Social Networks Applied. IEEE Intelligent Systems 20(1): 80-93 (2005)
67	EE	Sumit K. Sanghai, Pedro Domingos, Daniel S. Weld: Relational Dynamic Bayesian Networks. J. Artif. Intell. Res. (JAIR) 24: 759-797 (2005)
2004
66	EE	Pedro Domingos: Learning, Logic, and Probability: A Unified View. ALT 2004: 53
65	EE	Pedro Domingos: Real-World Learning with Markov Logic Networks. ECML 2004: 17
64	EE	Daniel Grossman, Pedro Domingos: Learning Bayesian network classifiers by maximizing conditional likelihood. ICML 2004
63	EE	Pedro Domingos: Learning, Logic, and Probability: A Unified View. ILP 2004: 359
62	EE	Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. Sanghai, Deepak Verma: Adversarial classification. KDD 2004: 99-108
61	EE	Pedro Domingos: Real-World Learning with Markov Logic Networks. PKDD 2004: 17
60	EE	Robin Dhamankar, Yoonkyong Lee, AnHai Doan, Alon Y. Halevy, Pedro Domingos: iMAP: Discovering Complex Mappings between Database Schemas. SIGMOD Conference 2004: 383-394
59		AnHai Doan, Jayant Madhavan, Pedro Domingos, Alon Y. Halevy: Ontology Matching: A Machine Learning Approach. Handbook on Ontologies 2004: 385-404
58		Matthew Richardson, Pedro Domingos: Combining Link and Content Information in Web Search. Web Dynamics 2004: 179-194
2003
57		Lise Getoor, Ted E. Senator, Pedro Domingos, Christos Faloutsos: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24 - 27, 2003 ACM 2003
56	EE	Pedro Domingos, Matt Richardson: Learning from Networks of Examples. EPIA 2003: 5
55		Matt Richardson, Pedro Domingos: Learning with Knowledge from Multiple Experts. ICML 2003: 624-631
54		Daniel S. Weld, Corin R. Anderson, Pedro Domingos, Oren Etzioni, Krzysztof Gajos, Tessa A. Lau, Steven A. Wolfman: Automatically Personalizing User Interfaces. IJCAI 2003: 1613-1619
53	EE	Matthew Richardson, Rakesh Agrawal, Pedro Domingos: Trust Management for the Semantic Web. International Semantic Web Conference 2003: 351-368
52	EE	Matthew Richardson, Pedro Domingos: Building large knowledge bases by mass collaboration. K-CAP 2003: 129-137
51	EE	Tessa A. Lau, Pedro Domingos, Daniel S. Weld: Learning programs from traces using version space algebra. K-CAP 2003: 36-43
50		AnHai Doan, Pedro Domingos, Alon Y. Halevy: Learning to Match the Schemas of Data Sources: A Multistrategy Approach. Machine Learning 50(3): 279-301 (2003)
49	EE	Foster J. Provost, Pedro Domingos: Tree Induction for Probability-Based Ranking. Machine Learning 52(3): 199-215 (2003)
48	EE	Tessa A. Lau, Steven A. Wolfman, Pedro Domingos, Daniel S. Weld: Programming by Demonstration Using Version Space Algebra. Machine Learning 53(1-2): 111-156 (2003)
47	EE	Pedro Domingos: Prospects and challenges for multi-relational data mining. SIGKDD Explorations 5(1): 80-83 (2003)
46	EE	AnHai Doan, Jayant Madhavan, Robin Dhamankar, Pedro Domingos, Alon Y. Halevy: Learning to match ontologies on the Semantic Web. VLDB J. 12(4): 303-319 (2003)
2002
45		Jayant Madhavan, Philip A. Bernstein, Pedro Domingos, Alon Y. Halevy: Representing and Reasoning about Mappings between Domain Models. AAAI/IAAI 2002: 80-86
44	EE	Corin R. Anderson, Pedro Domingos, Daniel S. Weld: Relational Markov models and their application to adaptive web navigation. KDD 2002: 143-152
43	EE	Geoff Hulten, Pedro Domingos: Mining complex models from arbitrarily large databases in constant time. KDD 2002: 525-531
42	EE	Matt Richardson, Pedro Domingos: Mining knowledge-sharing sites for viral marketing. KDD 2002: 61-70
41	EE	AnHai Doan, Jayant Madhavan, Pedro Domingos, Alon Y. Halevy: Learning to map between ontologies on the semantic web. WWW 2002: 662-673
40	EE	Pedro Domingos: When and How to Subsample: Report on the KDD-2001 Panel. SIGKDD Explorations 3(2): 74-75 (2002)
2001
39	EE	Pedro Domingos, Geoff Hulten: Catching up with the Data: Research Issues in Mining Data Streams. DMKD 2001
38		Pedro Domingos, Geoff Hulten: A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering. ICML 2001: 106-113
37		Corin R. Anderson, Pedro Domingos, Daniel S. Weld: Adaptive Web Navigation for Wireless Devices. IJCAI 2001: 879-884
36	EE	Steven A. Wolfman, Tessa A. Lau, Pedro Domingos, Daniel S. Weld: Mixed initiative interfaces for learning tasks: SMARTedit talks back. Intelligent User Interfaces 2001: 167-174
35	EE	Pedro Domingos, Matt Richardson: Mining the network value of customers. KDD 2001: 57-66
34	EE	Geoff Hulten, Laurie Spencer, Pedro Domingos: Mining time-changing data streams. KDD 2001: 97-106
33	EE	Matt Richardson, Pedro Domingos: The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank. NIPS 2001: 1441-1448
32	EE	Pedro Domingos, Geoff Hulten: Learning from Infinite Data in Finite Time. NIPS 2001: 673-680
31	EE	AnHai Doan, Pedro Domingos, Alon Y. Halevy: Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach. SIGMOD Conference 2001: 509-520
30	EE	Corin R. Anderson, Pedro Domingos, Daniel S. Weld: Personalizing Web Sites for Mobile Users. WWW 2001: 565-575
2000
29		Pedro Domingos: A Unified Bias-Variance Decomposition for Zero-One and Squared Loss. AAAI/IAAI 2000: 564-569
28	EE	Pedro Domingos: Beyond Occam's Razor: Process-Oriented Evaluation. ECML 2000: 3
27		Pedro Domingos: Bayesian Averaging of Classifiers and the Overfitting Problem. ICML 2000: 223-230
26		Pedro Domingos: A Unifeid Bias-Variance Decomposition and its Applications. ICML 2000: 231-238
25		Tessa A. Lau, Pedro Domingos, Daniel S. Weld: Version Space Algebra and its Application to Programming by Demonstration. ICML 2000: 527-534
24	EE	Pedro Domingos, Geoff Hulten: Mining high-speed data streams. KDD 2000: 71-80
23	EE	AnHai Doan, Pedro Domingos, Alon Y. Levy: Learning Source Description for Data Integration. WebDB (Informal Proceedings) 2000: 81-86
1999
22		Pedro Domingos: Process-Oriented Estimation of Generalization Error. IJCAI 1999: 714-721
21	EE	Pedro Domingos: MetaCost: A General Method for Making Classifiers Cost-Sensitive. KDD 1999: 155-164
20		Pedro Domingos: The Role of Occam's Razor in Knowledge Discovery. Data Min. Knowl. Discov. 3(4): 409-425 (1999)
1998
19		Pedro Domingos: A Process-Oriented Heuristic for Model Selection. ICML 1998: 127-135
18		Pedro Domingos: Occam's Two Razors: The Sharp and the Blunt. KDD 1998: 37-43
17	EE	Pedro Domingos: Knowledge Discovery Via Multiple Models. Intell. Data Anal. 2(1-4): 187-202 (1998)
1997
16		Pedro Domingos: A Comparison of Model Averaging Methods in Foreign Exchange Prediction. AAAI/IAAI 1997: 828
15		Pedro Domingos: Learning Multiple Models without Sacrificing Comprehensibility. AAAI/IAAI 1997: 829
14		Pedro Domingos: Knowledge Acquisition form Examples Vis Multiple Models. ICML 1997: 98-106
13		Pedro Domingos: Why Does Bagging Work? A Bayesian Account and its Implications. KDD 1997: 155-158
12		Pedro Domingos: Control-Sensitive Feature Selection for Lazy Learners. Artif. Intell. Rev. 11(1-5): 227-253 (1997)
11		Pedro Domingos, Michael J. Pazzani: On the Optimality of the Simple Bayesian Classifier under Zero-One Loss. Machine Learning 29(2-3): 103-130 (1997)
1996
10		Pedro Domingos: Towards a Unified Approach to Concept Learning. AAAI/IAAI, Vol. 2 1996: 1361
9		Pedro Domingos: Fast Discovery of Simple Rules. AAAI/IAAI, Vol. 2 1996: 1384
8		Pedro Domingos: Multistrategy Learning: A Case Study. AAAI/IAAI, Vol. 2 1996: 1385
7		Pedro Domingos, Michael J. Pazzani: Simple Bayesian Classifiers Do Not Assume Independence. AAAI/IAAI, Vol. 2 1996: 1386
6		Pedro Domingos, Michael J. Pazzani: Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier. ICML 1996: 105-112
5		Pedro Domingos: Efficient Specific-to-General Rule Induction. KDD 1996: 319-322
4		Pedro Domingos: Linear-Time Rule Induction. KDD 1996: 96-101
3		Pedro Domingos: Unifying Instance-Based and Rule-Based Induction. Machine Learning 24(2): 141-168 (1996)
1995
2		Pedro Domingos: Rule Induction and Instance-Based Learning: A Unified Approach. IJCAI 1995: 1226-1232
1994
1		Pedro Domingos: The RISE System: Conquering without Separating. ICTAI 1994: 704-707

Coauthor Index

1 Rakesh Agrawal [53]

2 Corin R. Anderson [30] [37] [44] [54]

3 Michael L. Anderson [69]

4 Thomas Barkowsky [69]

5 Philip A. Bernstein [45]

6 Pauline M. Berry (Pauline Berry) [69]

7 Douglas S. Blank [69]

8 Timothy Chklovski [69]

9 Nilesh N. Dalvi [62]

10 Robin Dhamankar [46] [60]

11 Li Ding [68]

12 AnHai Doan [23] [31] [41] [46] [50] [59] [60]

13 Marek J. Druzdzel [69]

14 Oren Etzioni [54]

15 Christos Faloutsos [57]

16 Timothy W. Finin (Tim Finin) [68]

17 Christian Freksa [69]

18 Krzysztof Gajos [54]

19 John Gersh [69]

20 Lise Getoor [57]

21 Jennifer Golbeck [68]

22 Daniel Grossman [64]

23 Alon Y. Halevy (Alon Y. Levy) [23] [31] [41] [45] [46] [50] [59] [60]

24 Mary Hegarty [69]

25 Geoff Hulten [24] [32] [34] [38] [39] [43]

26 Anupam Joshi [68]

27 Stanley Kok [73] [81] [87]

28 Tessa A. Lau [25] [36] [48] [51] [54]

29 Yoonkyong Lee [60]

30 Tze-Yun Leong [69]

31 Henry Lieberman [69]

32 Daniel Lowd [72] [85] [86]

33 Ric K. Lowe [69]

34 Susann Luperfoy [69]

35 Jayant Madhavan [41] [45] [46] [59]

36 Mausam [62]

37 Lisa Meeden [69]

38 Rada Mihalcea [69]

39 Peter Mika [68]

40 David P. Miller [69]

41 Horácio C. Neto [74]

42 Andrzej Nowak [68]

43 Tim Oates [69]

44 Michael J. Pazzani [6] [7] [11]

45 Hoifung Poon [81] [82] [88]

46 Robert Popp [69]

47 Foster J. Provost [49]

48 Matt Richardson [33] [35] [42] [55] [56]

49 Matthew Richardson [52] [53] [58] [76] [81]

50 Sumit K. Sanghai [62] [67]

51 Nathan Schurr [69]

52 Ted E. Senator [57]

53 Daniel Shapiro [69]

54 Fernando M. Silva [74]

55 Push Singh [69]

56 Parag Singla [70] [71] [75] [78] [81] [83]

57 Laurie Spencer [34]

58 Steffen Staab [68]

59 Robin R. Vallacher [68]

60 Deepak Verma [62]

61 Daniel S. Weld [25] [30] [36] [37] [44] [48] [51] [54] [67]

62 Steven A. Wolfman [36] [48] [54]

63 John Yen [69]

Colors in the list of coauthors

DBLP: [Home | Search: Author, Title | Conferences | Journals]

Michael Ley (ley@uni-trier.de) Thu Dec 27 04:59:51 2007

1	Rakesh Agrawal	[53]
2	Corin R. Anderson	[30] [37] [44] [54]
3	Michael L. Anderson	[69]
4	Thomas Barkowsky	[69]
5	Philip A. Bernstein	[45]
6	Pauline M. Berry (Pauline Berry)	[69]
7	Douglas S. Blank	[69]
8	Timothy Chklovski	[69]
9	Nilesh N. Dalvi	[62]
10	Robin Dhamankar	[46] [60]
11	Li Ding	[68]
12	AnHai Doan	[23] [31] [41] [46] [50] [59] [60]
13	Marek J. Druzdzel	[69]
14	Oren Etzioni	[54]
15	Christos Faloutsos	[57]
16	Timothy W. Finin (Tim Finin)	[68]
17	Christian Freksa	[69]
18	Krzysztof Gajos	[54]
19	John Gersh	[69]
20	Lise Getoor	[57]
21	Jennifer Golbeck	[68]
22	Daniel Grossman	[64]
23	Alon Y. Halevy (Alon Y. Levy)	[23] [31] [41] [45] [46] [50] [59] [60]
24	Mary Hegarty	[69]
25	Geoff Hulten	[24] [32] [34] [38] [39] [43]
26	Anupam Joshi	[68]
27	Stanley Kok	[73] [81] [87]
28	Tessa A. Lau	[25] [36] [48] [51] [54]
29	Yoonkyong Lee	[60]
30	Tze-Yun Leong	[69]
31	Henry Lieberman	[69]
32	Daniel Lowd	[72] [85] [86]
33	Ric K. Lowe	[69]
34	Susann Luperfoy	[69]
35	Jayant Madhavan	[41] [45] [46] [59]
36	Mausam	[62]
37	Lisa Meeden	[69]
38	Rada Mihalcea	[69]
39	Peter Mika	[68]
40	David P. Miller	[69]
41	Horácio C. Neto	[74]
42	Andrzej Nowak	[68]
43	Tim Oates	[69]
44	Michael J. Pazzani	[6] [7] [11]
45	Hoifung Poon	[81] [82] [88]
46	Robert Popp	[69]
47	Foster J. Provost	[49]
48	Matt Richardson	[33] [35] [42] [55] [56]
49	Matthew Richardson	[52] [53] [58] [76] [81]
50	Sumit K. Sanghai	[62] [67]
51	Nathan Schurr	[69]
52	Ted E. Senator	[57]
53	Daniel Shapiro	[69]
54	Fernando M. Silva	[74]
55	Push Singh	[69]
56	Parag Singla	[70] [71] [75] [78] [81] [83]
57	Laurie Spencer	[34]
58	Steffen Staab	[68]
59	Robin R. Vallacher	[68]
60	Deepak Verma	[62]
61	Daniel S. Weld	[25] [30] [36] [37] [44] [48] [51] [54] [67]
62	Steven A. Wolfman	[36] [48] [54]
63	John Yen	[69]