Gary M. Weiss

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Jeffrey W. LockhartUniversity of ChicagoVerified email at uchicago.edu
Foster ProvostProfessor, New York UniversityVerified email at stern.nyu.edu
Haym HirshComputer Science, Cornell UniversityVerified email at cornell.edu
Thaier Hayajneh, Ph. D., SMIEEEFordham Center for Cybersecurity, Fordham University, New York, USAVerified email at fordham.edu
Tony PulickalSolutions Engineer, HashiCorpVerified email at pulickal.net
ye tianBiogen IdecVerified email at sas.upenn.edu
Bianca ZadroznyIBM Research BrasilVerified email at br.ibm.com
Maytal Saar-TsechanskyThe University of Texas at AustinVerified email at mccombs.utexas.edu
Yijun ZhaoFordham UniversityVerified email at fordham.edu
Andrew H JohnstonFordham UniversityVerified email at fordham.edu
Md Zakirul Alam BhuiyanComp. & Info. Sciences, Fordham University (Highly-Cited Researcher, The Rising Star of Science)Verified email at fordham.edu
Daniel D LeedsFordham UniversityVerified email at fordham.edu
Robert StahlbockVerified email at uni-hamburg.de
Dr. Mahmoud Abou-NasrFord Motor CompanyVerified email at ieee.org
Qiang MaSponsored Products, AmazonVerified email at amazon.com
Diane LitmanUniversity of PittsburghVerified email at cs.pitt.edu
Yuhan HaoNew York University, New York Genome CenterVerified email at nyu.edu
Stefan LessmannProfessor of Information Systems, Humboldt-University of BerlinVerified email at hu-berlin.de
Stuart M. BrownAssociate Professor of Cell Biology, NYU School of MedicineVerified email at nyumc.org
Sven F. CroneAssistant Professor of Business Analytics, Lancaster UniversityVerified email at lancaster.ac.uk

Gary M. Weiss

Dept. of Computer & Info. Science, Fordham University

Verified email at fordham.edu - Homepage

Data Science Class Imbalance Behavioral Biometrics Activity Recognition Educational Data Mining


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Activity recognition using cell phone accelerometers JR Kwapisz, GM Weiss, SA Moore ACM SigKDD Explorations Newsletter 12 (2), 74-82, 2011	3611	2011
Mining with rarity: a unifying framework GM Weiss ACM Sigkdd Explorations Newsletter 6 (1), 7-19, 2004	1999	2004
Learning when training data are costly: The effect of class distribution on tree induction GM Weiss, F Provost Journal of artificial intelligence research 19, 315-354, 2003	1285	2003
The effect of class distribution on classifier learning: an empirical study GM Weiss, F Provost	651	2001
Cell phone-based biometric identification JR Kwapisz, GM Weiss, SA Moore 2010 Fourth IEEE International Conference on Biometrics: Theory …, 2010	412	2010
Cost-sensitive learning vs. sampling: Which is best for handling unbalanced classes with unequal error costs? GM Weiss, K McCarthy, B Zabar Dmin 7 (35-41), 24, 2007	408	2007
Learning to Predict Rare Events in Event Sequences. GM Weiss, H Hirsh KDD 98, 359-363, 1998	405	1998
Smartphone and smartwatch-based biometrics using activities of daily living GM Weiss, K Yoneda, T Hayajneh Ieee Access 7, 133190-133202, 2019	379	2019
Smartwatch-based activity recognition: A machine learning approach GM Weiss, JL Timko, CM Gallagher, K Yoneda, AJ Schreiber 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics …, 2016	281	2016
Does cost-sensitive learning beat sampling for classifying rare classes? K McCarthy, B Zabar, G Weiss Proceedings of the 1st international workshop on Utility-based data mining …, 2005	258	2005
The impact of personalization on smartphone-based activity recognition GM Weiss, J Lockhart Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012	254	2012
Design considerations for the WISDM smart phone-based sensor mining architecture JW Lockhart, GM Weiss, JC Xue, ST Gallagher, AB Grosner, TT Pulickal Proceedings of the Fifth International Workshop on Knowledge Discovery from …, 2011	204	2011
Smartwatch-based biometric gait recognition AH Johnston, GM Weiss 2015 IEEE 7th International Conference on Biometrics Theory, Applications …, 2015	194	2015
Applications of mobile activity recognition JW Lockhart, T Pulickal, GM Weiss Proceedings of the 2012 ACM conference on ubiquitous computing, 1054-1058, 2012	177	2012
Data mining in telecommunications GM Weiss Data Mining and Knowledge Discovery Handbook, 1189-1201, 2005	167	2005
Learning with rare cases and small disjuncts GM Weiss Machine Learning Proceedings 1995, 558-565, 1995	144	1995
Foundations of imbalanced learning GM Weiss Imbalanced learning: Foundations, algorithms, and applications, 13-41, 2013	125	2013
Wisdm smartphone and smartwatch activity and biometrics dataset GM Weiss UCI Machine Learning Repository: WISDM Smartphone and Smartwatch Activity …, 2019	118	2019
A quantitative study of small disjuncts GM Weiss, H Hirsh AAAI/IAAI 2000 (665–670), 15, 2000	118	2000
The impact of small disjuncts on classifier learning GM Weiss Data mining: Special issue in annals of information systems, 193-226, 2009	97	2009

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