Pedro Domingos Papers on DiSC'04 Adversarial Classification iMAP: Discovering Complex Mappings between Database Schemas Publications Note: Links lead to the DBLP on the Web. Pedro Domingos Pedro Domingos: Learning, Logic, and Probability: A Unified View. ALT 2004 : 53 Pedro Domingos: Real-World Learning with Markov Logic Networks. ECML 2004 : 17 Daniel Grossman , Pedro Domingos: Learning Bayesian network classifiers by maximizing conditional likelihood. ICML 2004 Pedro Domingos: Learning, Logic, and Probability: A Unified View. ILP 2004 : 359 Nilesh N. Dalvi , Pedro Domingos, Mausam , Sumit Sanghai , Deepak Verma : Adversarial classification. KDD 2004 : 99-108 Pedro Domingos: Real-World Learning with Markov Logic Networks. PKDD 2004 : 17 Robin Dhamankar , Yoonkyong Lee , AnHai Doan , Alon Y. Halevy , Pedro Domingos: iMAP: Discovering Complex Mappings between Database Schemas. SIGMOD Conference 2004 : 383-394 AnHai Doan , Jayant Madhavan , Pedro Domingos, Alon Y. Halevy : Ontology Matching: A Machine Learning Approach. Handbook on Ontologies 2004 : 385-404 Matthew Richardson , Pedro Domingos: Combining Link and Content Information in Web Search. Web Dynamics 2004 : 179-194 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 Pedro Domingos, Matt Richardson : Learning from Networks of Examples. EPIA 2003 : 5 Matt Richardson , Pedro Domingos: Learning with Knowledge from Multiple Experts. ICML 2003 : 624-631 Daniel S. Weld , Corin R. Anderson , Pedro Domingos, Oren Etzioni , Krzysztof Gajos , Tessa A. Lau , Steve A. Wolfman : Automatically Personalizing User Interfaces. IJCAI 2003 : 1613-1619 Sumit Sanghai , Pedro Domingos, Daniel S. Weld : Dynamic Probabilistic Relational Models. IJCAI 2003 : 992-1002 Matthew Richardson , Rakesh Agrawal , Pedro Domingos: Trust Management for the Semantic Web. International Semantic Web Conference 2003 : 351-368 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) Foster J. Provost , Pedro Domingos: Tree Induction for Probability-Based Ranking. Machine Learning 52 (3): 199-215 (2003) 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) Pedro Domingos: Prospects and challenges for multi-relational data mining. SIGKDD Explorations 5 (1): 80-83 (2003) 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) Jayant Madhavan , Philip A. Bernstein , Pedro Domingos, Alon Y. Halevy : Representing and Reasoning about Mappings between Domain Models. AAAI/IAAI 2002 : 80-86 Corin R. Anderson , Pedro Domingos, Daniel S. Weld : Relational Markov models and their application to adaptive web navigation. KDD 2002 : 143-152 Geoff Hulten , Pedro Domingos: Mining complex models from arbitrarily large databases in constant time. KDD 2002 : 525-531 Matt Richardson , Pedro Domingos: Mining knowledge-sharing sites for viral marketing. KDD 2002 : 61-70 AnHai Doan , Jayant Madhavan , Pedro Domingos, Alon Y. Halevy : Learning to map between ontologies on the semantic web. WWW 2002 : 662-673 Pedro Domingos: When and How to Subsample: Report on the KDD-2001 Panel. SIGKDD Explorations 3 (2): 74-75 (2002) Pedro Domingos, Geoff Hulten : Catching up with the Data: Research Issues in Mining Data Streams. DMKD 2001 Pedro Domingos, Geoff Hulten : A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering. ICML 2001 : 106-113 Corin R. Anderson , Pedro Domingos, Daniel S. Weld : Adaptive Web Navigation for Wireless Devices. IJCAI 2001 : 879-884 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 Pedro Domingos, Matt Richardson : Mining the network value of customers. KDD 2001 : 57-66 Geoff Hulten , Laurie Spencer , Pedro Domingos: Mining time-changing data streams. KDD 2001 : 97-106 Matt Richardson , Pedro Domingos: The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank. NIPS 2001 : 1441-1448 Pedro Domingos, Geoff Hulten : Learning from Infinite Data in Finite Time. NIPS 2001 : 673-680 AnHai Doan , Pedro Domingos, Alon Y. Halevy : Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach. SIGMOD Conference 2001 Corin R. Anderson , Pedro Domingos, Daniel S. Weld : Personalizing Web Sites for Mobile Users. WWW 2001 : 565-575 Pedro Domingos: A Unified Bias-Variance Decomposition for Zero-One and Squared Loss. AAAI/IAAI 2000 : 564-569 Pedro Domingos: Beyond Occam's Razor: Process-Oriented Evaluation. ECML 2000 : 3 Pedro Domingos: Bayesian Averaging of Classifiers and the Overfitting Problem. ICML 2000 : 223-230 Pedro Domingos: A Unifeid Bias-Variance Decomposition and its Applications. ICML 2000 : 231-238 Tessa A. Lau , Pedro Domingos, Daniel S. Weld : Version Space Algebra and its Application to Programming by Demonstration. ICML 2000 : 527-534 Pedro Domingos, Geoff Hulten : Mining high-speed data streams. KDD 2000 : 71-80 AnHai Doan , Pedro Domingos, Alon Y. Levy : Learning Source Description for Data Integration. WebDB (Informal Proceedings) 2000 : 81-86 Pedro Domingos: Process-Oriented Estimation of Generalization Error. IJCAI 1999 : 714-721 Pedro Domingos: MetaCost: A General Method for Making Classifiers Cost-Sensitive. KDD 1999 : 155-164 Pedro Domingos: The Role of Occam's Razor in Knowledge Discovery. Data Min. Knowl. Discov. 3 (4): 409-425 (1999) Pedro Domingos: A Process-Oriented Heuristic for Model Selection. ICML 1998 : 127-135 Pedro Domingos: Occam's Two Razors: The Sharp and the Blunt. KDD 1998 : 37-43 Pedro Domingos: Knowledge Discovery Via Multiple Models. Intell. Data Anal. 2 (1-4): 187-202 (1998) Pedro Domingos: A Comparison of Model Averaging Methods in Foreign Exchange Prediction. AAAI/IAAI 1997 : 828 Pedro Domingos: Learning Multiple Models without Sacrificing Comprehensibility. AAAI/IAAI 1997 : 829 Pedro Domingos: Knowledge Acquisition form Examples Vis Multiple Models. ICML 1997 : 98-106 Pedro Domingos: Why Does Bagging Work? A Bayesian Account and its Implications. KDD 1997 : 155-158 Pedro Domingos: Control-Sensitive Feature Selection for Lazy Learners. Artif. Intell. Rev. 11 (1-5): 227-253 (1997) 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) Pedro Domingos: Towards a Unified Approach to Concept Learning. AAAI/IAAI, Vol. 2 1996 : 1361 Pedro Domingos: Fast Discovery of Simple Rules. AAAI/IAAI, Vol. 2 1996 : 1384 Pedro Domingos: Multistrategy Learning: A Case Study. AAAI/IAAI, Vol. 2 1996 : 1385 Pedro Domingos, Michael J. Pazzani : Simple Bayesian Classifiers Do Not Assume Independence. AAAI/IAAI, Vol. 2 1996 : 1386 Pedro Domingos, Michael J. Pazzani : Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier. ICML 1996 : 105-112 Pedro Domingos: Efficient Specific-to-General Rule Induction. KDD 1996 : 319-322 Pedro Domingos: Linear-Time Rule Induction. KDD 1996 : 96-101 Pedro Domingos: Unifying Instance-Based and Rule-Based Induction. Machine Learning 24 (2): 141-168 (1996) Pedro Domingos: Rule Induction and Instance-Based Learning: A Unified Approach. IJCAI 1995 : 1226-1232 Pedro Domingos: The RISE System: Conquering without Separating. ICTAI 1994 : 704-707 1 [ 51 ] 2 [ 30 ] [ 37 ] [ 44 ] [ 53 ] 3 [ 45 ] 4 [ 61 ] 5 [ 46 ] [ 59 ] 6 [ 23 ] [ 31 ] [ 41 ] [ 46 ] [ 50 ] [ 58 ] [ 59 ] 7 [ 53 ] 8 [ 56 ] 9 [ 53 ] 10 [ 56 ] 11 [ 63 ] 12 [ 31 ] [ 41 ] [ 45 ] [ 46 ] [ 50 ] [ 58 ] [ 59 ] 13 [ 24 ] [ 32 ] [ 34 ] [ 38 ] [ 39 ] [ 43 ] 14 [ 25 ] [ 36 ] [ 48 ] [ 53 ] 15 [ 59 ] 16 [ 23 ] 17 [ 41 ] [ 45 ] [ 46 ] [ 58 ] 18 [ 61 ] 19 [ 6 ] [ 7 ] [ 11 ] 20 [ 49 ] 21 [ 33 ] [ 35 ] [ 42 ] [ 54 ] [ 55 ] 22 [ 51 ] [ 57 ] 23 [ 52 ] [ 61 ] 24 [ 56 ] 25 [ 34 ] 26 [ 61 ] 27 [ 25 ] [ 30 ] [ 36 ] [ 37 ] [ 44 ] [ 48 ] [ 52 ] [ 53 ] 28 [ 53 ] 29 [ 36 ] [ 48 ] ©2005 Association for Computing Machinery