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Title:
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Pedro Domingos: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Pedro Domingos
    Linear-Time Rule Induction. [Citation Graph (2, 0)][DBLP]
    KDD, 1996, pp:96-101 [Conf]
  2. Pedro Domingos, Michael J. Pazzani
    Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier. [Citation Graph (1, 0)][DBLP]
    ICML, 1996, pp:105-112 [Conf]
  3. Pedro Domingos
    Unifying Instance-Based and Rule-Based Induction. [Citation Graph (1, 0)][DBLP]
    Machine Learning, 1996, v:24, n:2, pp:141-168 [Journal]
  4. Pedro Domingos
    A Unified Bias-Variance Decomposition for Zero-One and Squared Loss. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:564-569 [Conf]
  5. Pedro Domingos
    Towards a Unified Approach to Concept Learning. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 2, 1996, pp:1361- [Conf]
  6. Pedro Domingos
    Fast Discovery of Simple Rules. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 2, 1996, pp:1384- [Conf]
  7. Pedro Domingos
    Multistrategy Learning: A Case Study. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 2, 1996, pp:1385- [Conf]
  8. Pedro Domingos
    A Comparison of Model Averaging Methods in Foreign Exchange Prediction. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1997, pp:828- [Conf]
  9. Pedro Domingos
    Learning Multiple Models without Sacrificing Comprehensibility. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1997, pp:829- [Conf]
  10. Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla
    Unifying Logical and Statistical AI. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  11. Pedro Domingos, Michael J. Pazzani
    Simple Bayesian Classifiers Do Not Assume Independence. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 2, 1996, pp:1386- [Conf]
  12. Jayant Madhavan, Philip A. Bernstein, Pedro Domingos, Alon Y. Halevy
    Representing and Reasoning about Mappings between Domain Models. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2002, pp:80-86 [Conf]
  13. Hoifung Poon, Pedro Domingos
    Sound and Efficient Inference with Probabilistic and Deterministic Dependencies. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  14. Parag Singla, Pedro Domingos
    Discriminative Training of Markov Logic Networks. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:868-873 [Conf]
  15. Parag Singla, Pedro Domingos
    Memory-Efficient Inference in Relational Domains. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  16. Pedro Domingos
    Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP]
    ALT, 2004, pp:53- [Conf]
  17. Pedro Domingos, Geoff Hulten
    Catching up with the Data: Research Issues in Mining Data Streams. [Citation Graph (0, 0)][DBLP]
    DMKD, 2001, pp:- [Conf]
  18. Pedro Domingos
    Beyond Occam's Razor: Process-Oriented Evaluation. [Citation Graph (0, 0)][DBLP]
    ECML, 2000, pp:3- [Conf]
  19. Pedro Domingos
    Real-World Learning with Markov Logic Networks. [Citation Graph (0, 0)][DBLP]
    ECML, 2004, pp:17- [Conf]
  20. Pedro Domingos
    Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP]
    EKAW, 2006, pp:2- [Conf]
  21. Pedro Domingos, Matt Richardson
    Learning from Networks of Examples. [Citation Graph (0, 0)][DBLP]
    EPIA, 2003, pp:5- [Conf]
  22. Pedro Domingos, Fernando M. Silva, Horácio C. Neto
    An Efficient and Scalable Architecture for Neural Networks with Backpropagation Learning. [Citation Graph (0, 0)][DBLP]
    FPL, 2005, pp:89-94 [Conf]
  23. Pedro Domingos
    Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP]
    IBERAMIA-SBIA, 2006, pp:3- [Conf]
  24. Parag Singla, Pedro Domingos
    Entity Resolution with Markov Logic. [Citation Graph (0, 0)][DBLP]
    ICDM, 2006, pp:572-582 [Conf]
  25. Pedro Domingos
    Bayesian Averaging of Classifiers and the Overfitting Problem. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:223-230 [Conf]
  26. Pedro Domingos
    A Unifeid Bias-Variance Decomposition and its Applications. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:231-238 [Conf]
  27. Pedro Domingos
    Knowledge Acquisition form Examples Vis Multiple Models. [Citation Graph (0, 0)][DBLP]
    ICML, 1997, pp:98-106 [Conf]
  28. Pedro Domingos
    A Process-Oriented Heuristic for Model Selection. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:127-135 [Conf]
  29. Pedro Domingos, Geoff Hulten
    A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:106-113 [Conf]
  30. Daniel Grossman, Pedro Domingos
    Learning Bayesian network classifiers by maximizing conditional likelihood. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  31. Stanley Kok, Pedro Domingos
    Learning the structure of Markov logic networks. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:441-448 [Conf]
  32. Tessa A. Lau, Pedro Domingos, Daniel S. Weld
    Version Space Algebra and its Application to Programming by Demonstration. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:527-534 [Conf]
  33. Daniel Lowd, Pedro Domingos
    Naive Bayes models for probability estimation. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:529-536 [Conf]
  34. Matt Richardson, Pedro Domingos
    Learning with Knowledge from Multiple Experts. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:624-631 [Conf]
  35. Pedro Domingos
    The RISE System: Conquering without Separating. [Citation Graph (0, 0)][DBLP]
    ICTAI, 1994, pp:704-707 [Conf]
  36. Corin R. Anderson, Pedro Domingos, Daniel S. Weld
    Adaptive Web Navigation for Wireless Devices. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2001, pp:879-884 [Conf]
  37. Pedro Domingos
    Rule Induction and Instance-Based Learning: A Unified Approach. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1995, pp:1226-1232 [Conf]
  38. Pedro Domingos
    Process-Oriented Estimation of Generalization Error. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1999, pp:714-721 [Conf]
  39. Parag Singla, Pedro Domingos
    Collective Object Identification. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2005, pp:1636-1637 [Conf]
  40. Daniel S. Weld, Corin R. Anderson, Pedro Domingos, Oren Etzioni, Krzysztof Gajos, Tessa A. Lau, Steven A. Wolfman
    Automatically Personalizing User Interfaces. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2003, pp:1613-1619 [Conf]
  41. Daniel Lowd, Pedro Domingos
    Recursive Random Fields. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:950-955 [Conf]
  42. Pedro Domingos
    Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP]
    ILP, 2004, pp:359- [Conf]
  43. Steven A. Wolfman, Tessa A. Lau, Pedro Domingos, Daniel S. Weld
    Mixed initiative interfaces for learning tasks: SMARTedit talks back. [Citation Graph (0, 0)][DBLP]
    Intelligent User Interfaces, 2001, pp:167-174 [Conf]
  44. Matthew Richardson, Pedro Domingos
    Building large knowledge bases by mass collaboration. [Citation Graph (0, 0)][DBLP]
    K-CAP, 2003, pp:129-137 [Conf]
  45. Tessa A. Lau, Pedro Domingos, Daniel S. Weld
    Learning programs from traces using version space algebra. [Citation Graph (0, 0)][DBLP]
    K-CAP, 2003, pp:36-43 [Conf]
  46. Corin R. Anderson, Pedro Domingos, Daniel S. Weld
    Relational Markov models and their application to adaptive web navigation. [Citation Graph (0, 0)][DBLP]
    KDD, 2002, pp:143-152 [Conf]
  47. Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. Sanghai, Deepak Verma
    Adversarial classification. [Citation Graph (0, 0)][DBLP]
    KDD, 2004, pp:99-108 [Conf]
  48. Pedro Domingos
    Occam's Two Razors: The Sharp and the Blunt. [Citation Graph (0, 0)][DBLP]
    KDD, 1998, pp:37-43 [Conf]
  49. Pedro Domingos
    Efficient Specific-to-General Rule Induction. [Citation Graph (0, 0)][DBLP]
    KDD, 1996, pp:319-322 [Conf]
  50. Pedro Domingos
    Why Does Bagging Work? A Bayesian Account and its Implications. [Citation Graph (0, 0)][DBLP]
    KDD, 1997, pp:155-158 [Conf]
  51. Pedro Domingos
    MetaCost: A General Method for Making Classifiers Cost-Sensitive. [Citation Graph (0, 0)][DBLP]
    KDD, 1999, pp:155-164 [Conf]
  52. Pedro Domingos, Geoff Hulten
    Mining high-speed data streams. [Citation Graph (0, 0)][DBLP]
    KDD, 2000, pp:71-80 [Conf]
  53. Pedro Domingos, Matt Richardson
    Mining the network value of customers. [Citation Graph (0, 0)][DBLP]
    KDD, 2001, pp:57-66 [Conf]
  54. Geoff Hulten, Pedro Domingos
    Mining complex models from arbitrarily large databases in constant time. [Citation Graph (0, 0)][DBLP]
    KDD, 2002, pp:525-531 [Conf]
  55. Geoff Hulten, Laurie Spencer, Pedro Domingos
    Mining time-changing data streams. [Citation Graph (0, 0)][DBLP]
    KDD, 2001, pp:97-106 [Conf]
  56. Matt Richardson, Pedro Domingos
    Mining knowledge-sharing sites for viral marketing. [Citation Graph (0, 0)][DBLP]
    KDD, 2002, pp:61-70 [Conf]
  57. Pedro Domingos, Geoff Hulten
    Learning from Infinite Data in Finite Time. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:673-680 [Conf]
  58. Matt Richardson, Pedro Domingos
    The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1441-1448 [Conf]
  59. Pedro Domingos
    Real-World Learning with Markov Logic Networks. [Citation Graph (0, 0)][DBLP]
    PKDD, 2004, pp:17- [Conf]
  60. Parag Singla, Pedro Domingos
    Object Identification with Attribute-Mediated Dependences. [Citation Graph (0, 0)][DBLP]
    PKDD, 2005, pp:297-308 [Conf]
  61. Pedro Domingos
    Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP]
    PRICAI, 2006, pp:1- [Conf]
  62. Matthew Richardson, Rakesh Agrawal, Pedro Domingos
    Trust Management for the Semantic Web. [Citation Graph (0, 0)][DBLP]
    International Semantic Web Conference, 2003, pp:351-368 [Conf]
  63. AnHai Doan, Pedro Domingos, Alon Y. Halevy
    Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach. [Citation Graph (0, 0)][DBLP]
    SIGMOD Conference, 2001, pp:509-520 [Conf]
  64. Robin Dhamankar, Yoonkyong Lee, AnHai Doan, Alon Y. Halevy, Pedro Domingos
    iMAP: Discovering Complex Mappings between Database Schemas. [Citation Graph (0, 0)][DBLP]
    SIGMOD Conference, 2004, pp:383-394 [Conf]
  65. AnHai Doan, Pedro Domingos, Alon Y. Levy
    Learning Source Description for Data Integration. [Citation Graph (0, 0)][DBLP]
    WebDB (Informal Proceedings), 2000, pp:81-86 [Conf]
  66. Corin R. Anderson, Pedro Domingos, Daniel S. Weld
    Personalizing Web Sites for Mobile Users. [Citation Graph (0, 0)][DBLP]
    WWW, 2001, pp:565-575 [Conf]
  67. AnHai Doan, Jayant Madhavan, Pedro Domingos, Alon Y. Halevy
    Learning to map between ontologies on the semantic web. [Citation Graph (0, 0)][DBLP]
    WWW, 2002, pp:662-673 [Conf]
  68. 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. [Citation Graph (0, 0)][DBLP]
    AI Magazine, 2005, v:26, n:2, pp:87-92 [Journal]
  69. Pedro Domingos
    Control-Sensitive Feature Selection for Lazy Learners. [Citation Graph (0, 0)][DBLP]
    Artif. Intell. Rev., 1997, v:11, n:1-5, pp:227-253 [Journal]
  70. Pedro Domingos
    The Role of Occam's Razor in Knowledge Discovery. [Citation Graph (0, 0)][DBLP]
    Data Min. Knowl. Discov., 1999, v:3, n:4, pp:409-425 [Journal]
  71. Steffen Staab, Pedro Domingos, Peter Mika, Jennifer Golbeck, Li Ding, Timothy W. Finin, Anupam Joshi, Andrzej Nowak, Robin R. Vallacher
    Social Networks Applied. [Citation Graph (0, 0)][DBLP]
    IEEE Intelligent Systems, 2005, v:20, n:1, pp:80-93 [Journal]
  72. Pedro Domingos
    Knowledge Discovery Via Multiple Models. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 1998, v:2, n:1-4, pp:187-202 [Journal]
  73. AnHai Doan, Pedro Domingos, Alon Y. Halevy
    Learning to Match the Schemas of Data Sources: A Multistrategy Approach. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2003, v:50, n:3, pp:279-301 [Journal]
  74. Pedro Domingos, Michael J. Pazzani
    On the Optimality of the Simple Bayesian Classifier under Zero-One Loss. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:29, n:2-3, pp:103-130 [Journal]
  75. Tessa A. Lau, Steven A. Wolfman, Pedro Domingos, Daniel S. Weld
    Programming by Demonstration Using Version Space Algebra. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2003, v:53, n:1-2, pp:111-156 [Journal]
  76. Foster J. Provost, Pedro Domingos
    Tree Induction for Probability-Based Ranking. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2003, v:52, n:3, pp:199-215 [Journal]
  77. Matthew Richardson, Pedro Domingos
    Markov logic networks. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2006, v:62, n:1-2, pp:107-136 [Journal]
  78. Pedro Domingos
    When and How to Subsample: Report on the KDD-2001 Panel. [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2002, v:3, n:2, pp:74-75 [Journal]
  79. Pedro Domingos
    Prospects and challenges for multi-relational data mining. [Citation Graph (0, 0)][DBLP]
    SIGKDD Explorations, 2003, v:5, n:1, pp:80-83 [Journal]
  80. AnHai Doan, Jayant Madhavan, Robin Dhamankar, Pedro Domingos, Alon Y. Halevy
    Learning to match ontologies on the Semantic Web. [Citation Graph (0, 0)][DBLP]
    VLDB J., 2003, v:12, n:4, pp:303-319 [Journal]
  81. Hoifung Poon, Pedro Domingos
    Joint Inference in Information Extraction. [Citation Graph (0, 0)][DBLP]
    AAAI, 2007, pp:913-918 [Conf]
  82. Stanley Kok, Pedro Domingos
    Statistical predicate invention. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:433-440 [Conf]
  83. Daniel Lowd, Pedro Domingos
    Efficient Weight Learning for Markov Logic Networks. [Citation Graph (0, 0)][DBLP]
    PKDD, 2007, pp:200-211 [Conf]
  84. Pedro Domingos
    Toward knowledge-rich data mining. [Citation Graph (0, 0)][DBLP]
    Data Min. Knowl. Discov., 2007, v:15, n:1, pp:21-28 [Journal]
  85. Sumit K. Sanghai, Pedro Domingos, Daniel S. Weld
    Relational Dynamic Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2005, v:24, n:, pp:759-797 [Journal]

  86. Hybrid Markov Logic Networks. [Citation Graph (, )][DBLP]


  87. A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC. [Citation Graph (, )][DBLP]


  88. Lifted First-Order Belief Propagation. [Citation Graph (, )][DBLP]


  89. Efficient Lifting for Online Probabilistic Inference. [Citation Graph (, )][DBLP]


  90. Efficient Belief Propagation for Utility Maximization and Repeated Inference. [Citation Graph (, )][DBLP]


  91. Markov logic: a unifying language for knowledge and information management. [Citation Graph (, )][DBLP]


  92. Markov Logic in Infinite Domains. [Citation Graph (, )][DBLP]


  93. Learning Markov logic network structure via hypergraph lifting. [Citation Graph (, )][DBLP]


  94. Deep transfer via second-order Markov logic. [Citation Graph (, )][DBLP]


  95. Bottom-Up Learning of Markov Network Structure. [Citation Graph (, )][DBLP]


  96. Learning Markov Logic Networks Using Structural Motifs. [Citation Graph (, )][DBLP]


  97. Markov Logic. [Citation Graph (, )][DBLP]


  98. Extracting Semantic Networks from Text Via Relational Clustering. [Citation Graph (, )][DBLP]


  99. Just Add Weights: Markov Logic for the Semantic Web. [Citation Graph (, )][DBLP]


  100. Markov Logic: A Unifying Language for Structural and Statistical Pattern Recognition. [Citation Graph (, )][DBLP]


  101. Learning Arithmetic Circuits. [Citation Graph (, )][DBLP]


  102. Joint Unsupervised Coreference Resolution with Markov Logic. [Citation Graph (, )][DBLP]


  103. Unsupervised Semantic Parsing. [Citation Graph (, )][DBLP]


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