Gary M. Weiss

Gary M. Weiss, Jeffrey W. Lockhart: A comparison of alternative client/server architectures for ubiquitous mobile sensor-based applications. UbiComp 2012: 721-724

Jeffrey W. Lockhart, Tony Pulickal, Gary M. Weiss: Applications of mobile activity recognition. UbiComp 2012: 1054-1058

Foster J. Provost, Gary M. Weiss: Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction. CoRR abs/1106.4557 (2011)

Jennifer R. Kwapisz, Gary M. Weiss, Samuel Moore: Activity recognition using cell phone accelerometers. SIGKDD Explorations 12(2): 74-82 (2010)

Gary M. Weiss: Mining with Rare Cases. Data Mining and Knowledge Discovery Handbook 2010: 747-757

Gary M. Weiss: The Impact of Small Disjuncts on Classifier Learning. Data Mining 2010: 193-226

Robert Stahlbock, Sven F. Crone, Mahmoud Abou-Nasr, Hamid R. Arabnia, Nikolaos Kourentzes, Philippe Lenca, Wolfram-Manfred Lippe, Gary M. Weiss (Eds.): Proceedings of The 2010 International Conference on Data Mining, DMIN 2010, July 12-15, 2010, Las Vegas, Nevada, USA. CSREA Press 2010, isbn 1-60132-138-4

Gary M. Weiss: Data Mining in the Real World: Experiences, Challenges, and Recommendations. DMIN 2009: 124-130

Samuel Moore, Daniel D'Addario, James Kurinskas, Gary M. Weiss: Are Decision Trees Always Greener on the Open (Source) Side of the Fence? DMIN 2009: 185-188

Ye Tian, Gary M. Weiss, D. Frank Hsu, Qiang Ma: A Combinatorial Fusion Method for Feature Construction. DMIN 2009: 260-266

Jack Chongjie Xue, Gary M. Weiss: Quantification and semi-supervised classification methods for handling changes in class distribution. KDD 2009: 897-906

Gary M. Weiss, Bianca Zadrozny, Maytal Saar-Tsechansky: Guest editorial: special issue on utility-based data mining. Data Min. Knowl. Discov. 17(2): 129-135 (2008)

Gary M. Weiss, Ye Tian: Maximizing classifier utility when there are data acquisition and modeling costs. Data Min. Knowl. Discov. 17(2): 253-282 (2008)

Gary M. Weiss, Kate McCarthy, Bibi Zabar: Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs? DMIN 2007: 35-41

Gary M. Weiss, Ye Tian: Maximizing classifier utility when training data is costly. SIGKDD Explorations 8(2): 31-38 (2006)

Bianca Zadrozny, Gary M. Weiss, Maytal Saar-Tsechansky: UBDM 2006: Utility-Based Data Mining 2006 workshop report. SIGKDD Explorations 8(2): 98-101 (2006)

Gary M. Weiss, Maytal Saar-Tsechansky, Bianca Zadrozny: Report on UBDM-05: Workshop on Utility-Based Data Mining. SIGKDD Explorations 7(2): 145-147 (2005)

Gary M. Weiss: Mining with Rare Cases. The Data Mining and Knowledge Discovery Handbook 2005: 765-776

Gary M. Weiss: Data Mining in Telecommunications. The Data Mining and Knowledge Discovery Handbook 2005: 1189-1201

Gary M. Weiss: Mining with rarity: a unifying framework. SIGKDD Explorations 6(1): 7-19 (2004)

Gary M. Weiss, Foster J. Provost: Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction. J. Artif. Intell. Res. (JAIR) 19: 315-354 (2003)

Gary M. Weiss, Haym Hirsh: A Quantitative Study of Small Disjuncts. AAAI/IAAI 2000: 665-670

Gary M. Weiss, Johannes P. Ros: Implementing Design Patterns with Object-Oriented Rules. JOOP 11(7): 25-27, 35 (1998)

Gary M. Weiss, Johannes P. Ros, Anoop Singhal: ANSWER: Network Monitoring Using Object-Oriented Rules. AAAI/IAAI 1998: 1087-1093

Gary M. Weiss, Haym Hirsh: The Problem with Noise and Small Disjuncts. ICML 1998: 574-

Gary M. Weiss, Haym Hirsh: Learning to Predict Rare Events in Event Sequences. KDD 1998: 359-363

Gary M. Weiss: Learning with Rare Cases and Small Disjuncts. ICML 1995: 558-565