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Note: Links lead to the DBLP on the Web. Pedro Domingos 30 Pedro Domingos: When and How to Subsample: Report on the KDD-2001 Panel. SIGKDD Explorations 3 (2): 74-75 (2002) 29 Corin R. Anderson , Pedro Domingos, Daniel S. Weld : Adaptive Web Navigation for Wireless Devices. IJCAI 2001 : 879-884 28 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 27 Pedro Domingos, Matt Richardson : Mining the network value of customers. KDD 2001 : 57-66 26 Geoff Hulten , Laurie Spencer , Pedro Domingos: Mining time-changing data streams. KDD 2001 : 97-106 25 AnHai Doan , Pedro Domingos, Alon Y. Halevy : Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach. SIGMOD Conference 2001 24 Corin R. Anderson , Pedro Domingos, Daniel S. Weld : Personalizing Web Sites for Mobile Users. WWW 2001 : 565-575 23 Pedro Domingos: A Unified Bias-Variance Decomposition for Zero-One and Squared Loss. AAAI/IAAI 2000 : 564-569 22 Pedro Domingos: Beyond Occam's Razor: Process-Oriented Evaluation. ECML 2000 : 3 21 Pedro Domingos, Geoff Hulten : Mining high-speed data streams. KDD 2000 : 71-80 20 AnHai Doan , Pedro Domingos, Alon Y. Levy : Learning Source Description for Data Integration. WebDB (Informal Proceedings) 2000 : 81-86 19 Pedro Domingos: Process-Oriented Estimation of Generalization Error. IJCAI 1999 : 714-721 18 Pedro Domingos: MetaCost: A General Method for Making Classifiers Cost-Sensitive. KDD 1999 : 155-164 17 Pedro Domingos: The Role of Occam's Razor in Knowledge Discovery. Data Mining and Knowledge Discovery 3 (4): 409-425 (1999) 16 Pedro Domingos: Occam's Two Razors: The Sharp and the Blunt. KDD 1998 : 37-43 15 Pedro Domingos: A Comparison of Model Averaging Methods in Foreign Exchange Prediction. AAAI/IAAI 1997 : 828 14 Pedro Domingos: Learning Multiple Models without Sacrificing Comprehensibility. AAAI/IAAI 1997 : 829 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. Artificial Intelligence Review 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) 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) 2 Pedro Domingos: Rule Induction and Instance-Based Learning: A Unified Approach. IJCAI 1995 : 1226-1232 1 Pedro Domingos: The RISE System: Conquering without Separating. ICTAI 1994 : 704-707  DiSC'02 © 2003 Association for Computing Machinery |
