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Pedro Domingos :
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Pedro Domingos Linear-Time Rule Induction. [Citation Graph (2, 0)][DBLP ] KDD, 1996, pp:96-101 [Conf ] 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 ] 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 ] 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 ] Pedro Domingos Towards a Unified Approach to Concept Learning. [Citation Graph (0, 0)][DBLP ] AAAI/IAAI, Vol. 2, 1996, pp:1361- [Conf ] Pedro Domingos Fast Discovery of Simple Rules. [Citation Graph (0, 0)][DBLP ] AAAI/IAAI, Vol. 2, 1996, pp:1384- [Conf ] Pedro Domingos Multistrategy Learning: A Case Study. [Citation Graph (0, 0)][DBLP ] AAAI/IAAI, Vol. 2, 1996, pp:1385- [Conf ] Pedro Domingos A Comparison of Model Averaging Methods in Foreign Exchange Prediction. [Citation Graph (0, 0)][DBLP ] AAAI/IAAI, 1997, pp:828- [Conf ] Pedro Domingos Learning Multiple Models without Sacrificing Comprehensibility. [Citation Graph (0, 0)][DBLP ] AAAI/IAAI, 1997, pp:829- [Conf ] Pedro Domingos , Stanley Kok , Hoifung Poon , Matthew Richardson , Parag Singla Unifying Logical and Statistical AI. [Citation Graph (0, 0)][DBLP ] AAAI, 2006, pp:- [Conf ] 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 ] 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 ] Hoifung Poon , Pedro Domingos Sound and Efficient Inference with Probabilistic and Deterministic Dependencies. [Citation Graph (0, 0)][DBLP ] AAAI, 2006, pp:- [Conf ] Parag Singla , Pedro Domingos Discriminative Training of Markov Logic Networks. [Citation Graph (0, 0)][DBLP ] AAAI, 2005, pp:868-873 [Conf ] Parag Singla , Pedro Domingos Memory-Efficient Inference in Relational Domains. [Citation Graph (0, 0)][DBLP ] AAAI, 2006, pp:- [Conf ] Pedro Domingos Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP ] ALT, 2004, pp:53- [Conf ] Pedro Domingos , Geoff Hulten Catching up with the Data: Research Issues in Mining Data Streams. [Citation Graph (0, 0)][DBLP ] DMKD, 2001, pp:- [Conf ] Pedro Domingos Beyond Occam's Razor: Process-Oriented Evaluation. [Citation Graph (0, 0)][DBLP ] ECML, 2000, pp:3- [Conf ] Pedro Domingos Real-World Learning with Markov Logic Networks. [Citation Graph (0, 0)][DBLP ] ECML, 2004, pp:17- [Conf ] Pedro Domingos Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP ] EKAW, 2006, pp:2- [Conf ] Pedro Domingos , Matt Richardson Learning from Networks of Examples. [Citation Graph (0, 0)][DBLP ] EPIA, 2003, pp:5- [Conf ] 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 ] Pedro Domingos Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP ] IBERAMIA-SBIA, 2006, pp:3- [Conf ] Parag Singla , Pedro Domingos Entity Resolution with Markov Logic. [Citation Graph (0, 0)][DBLP ] ICDM, 2006, pp:572-582 [Conf ] Pedro Domingos Bayesian Averaging of Classifiers and the Overfitting Problem. [Citation Graph (0, 0)][DBLP ] ICML, 2000, pp:223-230 [Conf ] Pedro Domingos A Unifeid Bias-Variance Decomposition and its Applications. [Citation Graph (0, 0)][DBLP ] ICML, 2000, pp:231-238 [Conf ] Pedro Domingos Knowledge Acquisition form Examples Vis Multiple Models. [Citation Graph (0, 0)][DBLP ] ICML, 1997, pp:98-106 [Conf ] Pedro Domingos A Process-Oriented Heuristic for Model Selection. [Citation Graph (0, 0)][DBLP ] ICML, 1998, pp:127-135 [Conf ] 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 ] Daniel Grossman , Pedro Domingos Learning Bayesian network classifiers by maximizing conditional likelihood. [Citation Graph (0, 0)][DBLP ] ICML, 2004, pp:- [Conf ] Stanley Kok , Pedro Domingos Learning the structure of Markov logic networks. [Citation Graph (0, 0)][DBLP ] ICML, 2005, pp:441-448 [Conf ] 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 ] Daniel Lowd , Pedro Domingos Naive Bayes models for probability estimation. [Citation Graph (0, 0)][DBLP ] ICML, 2005, pp:529-536 [Conf ] Matt Richardson , Pedro Domingos Learning with Knowledge from Multiple Experts. [Citation Graph (0, 0)][DBLP ] ICML, 2003, pp:624-631 [Conf ] Pedro Domingos The RISE System: Conquering without Separating. [Citation Graph (0, 0)][DBLP ] ICTAI, 1994, pp:704-707 [Conf ] 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 ] Pedro Domingos Rule Induction and Instance-Based Learning: A Unified Approach. [Citation Graph (0, 0)][DBLP ] IJCAI, 1995, pp:1226-1232 [Conf ] Pedro Domingos Process-Oriented Estimation of Generalization Error. [Citation Graph (0, 0)][DBLP ] IJCAI, 1999, pp:714-721 [Conf ] Parag Singla , Pedro Domingos Collective Object Identification. [Citation Graph (0, 0)][DBLP ] IJCAI, 2005, pp:1636-1637 [Conf ] 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 ] Daniel Lowd , Pedro Domingos Recursive Random Fields. [Citation Graph (0, 0)][DBLP ] IJCAI, 2007, pp:950-955 [Conf ] Pedro Domingos Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP ] ILP, 2004, pp:359- [Conf ] 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 ] Matthew Richardson , Pedro Domingos Building large knowledge bases by mass collaboration. [Citation Graph (0, 0)][DBLP ] K-CAP, 2003, pp:129-137 [Conf ] 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 ] 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 ] Nilesh N. Dalvi , Pedro Domingos , Mausam , Sumit K. Sanghai , Deepak Verma Adversarial classification. [Citation Graph (0, 0)][DBLP ] KDD, 2004, pp:99-108 [Conf ] Pedro Domingos Occam's Two Razors: The Sharp and the Blunt. [Citation Graph (0, 0)][DBLP ] KDD, 1998, pp:37-43 [Conf ] Pedro Domingos Efficient Specific-to-General Rule Induction. [Citation Graph (0, 0)][DBLP ] KDD, 1996, pp:319-322 [Conf ] Pedro Domingos Why Does Bagging Work? A Bayesian Account and its Implications. [Citation Graph (0, 0)][DBLP ] KDD, 1997, pp:155-158 [Conf ] Pedro Domingos MetaCost: A General Method for Making Classifiers Cost-Sensitive. [Citation Graph (0, 0)][DBLP ] KDD, 1999, pp:155-164 [Conf ] Pedro Domingos , Geoff Hulten Mining high-speed data streams. [Citation Graph (0, 0)][DBLP ] KDD, 2000, pp:71-80 [Conf ] Pedro Domingos , Matt Richardson Mining the network value of customers. [Citation Graph (0, 0)][DBLP ] KDD, 2001, pp:57-66 [Conf ] 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 ] Geoff Hulten , Laurie Spencer , Pedro Domingos Mining time-changing data streams. [Citation Graph (0, 0)][DBLP ] KDD, 2001, pp:97-106 [Conf ] Matt Richardson , Pedro Domingos Mining knowledge-sharing sites for viral marketing. [Citation Graph (0, 0)][DBLP ] KDD, 2002, pp:61-70 [Conf ] Pedro Domingos , Geoff Hulten Learning from Infinite Data in Finite Time. [Citation Graph (0, 0)][DBLP ] NIPS, 2001, pp:673-680 [Conf ] 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 ] Pedro Domingos Real-World Learning with Markov Logic Networks. [Citation Graph (0, 0)][DBLP ] PKDD, 2004, pp:17- [Conf ] Parag Singla , Pedro Domingos Object Identification with Attribute-Mediated Dependences. [Citation Graph (0, 0)][DBLP ] PKDD, 2005, pp:297-308 [Conf ] Pedro Domingos Learning, Logic, and Probability: A Unified View. [Citation Graph (0, 0)][DBLP ] PRICAI, 2006, pp:1- [Conf ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] 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 ] Matthew Richardson , Pedro Domingos Markov logic networks. [Citation Graph (0, 0)][DBLP ] Machine Learning, 2006, v:62, n:1-2, pp:107-136 [Journal ] 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 ] 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 ] 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 ] Hoifung Poon , Pedro Domingos Joint Inference in Information Extraction. [Citation Graph (0, 0)][DBLP ] AAAI, 2007, pp:913-918 [Conf ] Stanley Kok , Pedro Domingos Statistical predicate invention. [Citation Graph (0, 0)][DBLP ] ICML, 2007, pp:433-440 [Conf ] Daniel Lowd , Pedro Domingos Efficient Weight Learning for Markov Logic Networks. [Citation Graph (0, 0)][DBLP ] PKDD, 2007, pp:200-211 [Conf ] 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 ] 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 ] Hybrid Markov Logic Networks. [Citation Graph (, )][DBLP ] A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC. [Citation Graph (, )][DBLP ] Lifted First-Order Belief Propagation. [Citation Graph (, )][DBLP ] Efficient Lifting for Online Probabilistic Inference. [Citation Graph (, )][DBLP ] Efficient Belief Propagation for Utility Maximization and Repeated Inference. [Citation Graph (, )][DBLP ] Markov logic: a unifying language for knowledge and information management. [Citation Graph (, )][DBLP ] Markov Logic in Infinite Domains. [Citation Graph (, )][DBLP ] Learning Markov logic network structure via hypergraph lifting. [Citation Graph (, )][DBLP ] Deep transfer via second-order Markov logic. [Citation Graph (, )][DBLP ] Bottom-Up Learning of Markov Network Structure. [Citation Graph (, )][DBLP ] Learning Markov Logic Networks Using Structural Motifs. [Citation Graph (, )][DBLP ] Markov Logic. [Citation Graph (, )][DBLP ] Extracting Semantic Networks from Text Via Relational Clustering. [Citation Graph (, )][DBLP ] Just Add Weights: Markov Logic for the Semantic Web. [Citation Graph (, )][DBLP ] Markov Logic: A Unifying Language for Structural and Statistical Pattern Recognition. [Citation Graph (, )][DBLP ] Learning Arithmetic Circuits. [Citation Graph (, )][DBLP ] Joint Unsupervised Coreference Resolution with Markov Logic. [Citation Graph (, )][DBLP ] Unsupervised Semantic Parsing. [Citation Graph (, )][DBLP ] Search in 0.029secs, Finished in 0.032secs