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ORCIDGary Weiss 0001
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- affiliation: Fordham University, New York, NY, USA
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2020 – today
- 2024
[c39]Hyun Jeong, Gary M. Weiss, Audrey Leung, Daniel D. Leeds:
The Construction and Analysis of Course Grades Across Public Universities. EDM 2024- [c38]Fernando Martinez, Gary M. Weiss, Miguel Palma, Haoran Xue, Alexander Borelli, Yijun Zhao:
GPT vs. Llama2: Which Comes Closer to Human Writing? EDM 2024 - [c37]Yijun Zhao, Zhengxin Qi, Son Tung Do, John Grossi, Jee Hun Kang, Gary M. Weiss:
Predicting GRE Scores from Application Materials in Test-Optional Admissions. EDM 2024 - [c36]Yi Ding, Daniel D. Leeds, Yijun Zhao, Gary Weiss:
Introduction to the Minitrack on Educational Data Mining for Decision Making. HICSS 2024: 1275 - [c35]Yijun Zhao, Tianyu Wang, Douglas Mensah, Ellise Parnoff, Siyi He, Gary Weiss:
A Quantitative Machine Learning Approach to Evaluating Letters of Recommendation. HICSS 2024: 1276-1284 - 2023
- [c34]Gary M. Weiss, Luisa A. L. Rosa, Hyun Jeong, Daniel D. Leeds:
An Analysis of Grading Patterns in Undergraduate University Courses. COMPSAC 2023: 310-315 - 2022
- [c33]Gary Weiss, Erik Brown, Michael Riad-Zaky, Ruby Iannone, Daniel D. Leeds:
Assessing Instructor Effectiveness Based on Future Student Performance. EDM 2022 - [c32]Gary Weiss, Joseph Denham, Daniel D. Leeds:
The Impact of Semester Gaps on Student Grades. EDM 2022 - [c31]Daniel D. Leeds, Cody Chen, Yijun Zhao, Fiza Metla, James Guest, Gary Weiss:
Generalized Sequential Pattern Mining of Undergraduate Courses. EDM 2022 - 2021
- [c30]Gary Weiss, Nam Nguyen, Karla Dominguez, Daniel D. Leeds:
Identifying Hubs in Undergraduate Course Networks Based on Scaled Co-Enrollments. EDM 2021 - [c29]Tess Gutenbrunner, Daniel D. Leeds, Spencer Ross, Michael Riad-Zaky, Gary Weiss:
Measuring the Academic Impact of Course Sequencing using Student Grade Data. EDM 2021 - [c28]Daniel D. Leeds, Tianyi Zhang, Gary Weiss:
Mining Course Groupings based on Academic Performance. EDM 2021 - [i2]Gary M. Weiss, Nam Nguyen, Karla Dominguez, Daniel D. Leeds:
Identifying Hubs in Undergraduate Course Networks Based on Scaled Co-Enrollments: Extended Version. CoRR abs/2104.14500 (2021) - 2020
- [j12]Md. Zakirul Alam Bhuiyan
, Jie Wu, Gary M. Weiss, Thaier Hayajneh, Tian Wang, Guojun Wang:
Event Detection Through Differential Pattern Mining in Cyber-Physical Systems. IEEE Trans. Big Data 6(4): 652-665 (2020) - [c27]Yijun Zhao, Qiangwen Xu, Ming Chen, Gary Weiss:
Predicting Student Performance in a Master's Program in Data Science using Admissions Data. EDM 2020 - [c26]Samuel Alexander Stein, Gary M. Weiss, Yiwen Chen, Daniel D. Leeds:
A College Major Recommendation System. RecSys 2020: 640-644
2010 – 2019
- 2019
- [j11]Gary M. Weiss, Kenichi Yoneda, Thaier Hayajneh:
Smartphone and Smartwatch-Based Biometrics Using Activities of Daily Living. IEEE Access 7: 133190-133202 (2019) - [p6]Gary M. Weiss, Md. Zakirul Alam Bhuiyan:
An Overview of Wearable Computing. Mission-Oriented Sensor Networks and Systems (2) 2019: 313-349 - [p5]Md. Zakirul Alam Bhuiyan, Gary M. Weiss, Tian Wang, Geyong Min:
Mobile Target Tracking with Multiple Objectives in Wireless Sensor Networks. Mission-Oriented Sensor Networks and Systems (1) 2019: 437-495 - [d1]Gary Weiss:
WISDM Smartphone and Smartwatch Activity and Biometrics Dataset. UCI Machine Learning Repository, 2019
- 2018
- [j10]Yuhan Hao, Gary M. Weiss, Stuart M. Brown:
Identification of Candidate Genes Responsible for Age-related Macular Degeneration using Microarray Data. Int. J. Serv. Sci. Manag. Eng. Technol. 9(2): 33-60 (2018) - [c25]Luís Torgo, Stan Matwin, Gary Weiss, Nuno Moniz, Paula Branco:
Cost-Sensitive Learning: Preface. COST@SDM 2018: 1-3 - 2017
- [c24]Md. Zakirul Alam Bhuiyan, Tian Wang, Thaier Hayajneh, Gary M. Weiss:
Maintaining the Balance between Privacy and Data Integrity in Internet of Things. ICMSS 2017: 177-182 - [c23]Andrew H. Johnston, Gary M. Weiss:
Identifying sunni extremist propaganda with deep learning. SSCI 2017: 1-6 - [c22]Francesco Ciuffo, Gary M. Weiss:
Smartwatch-based transcription biometrics. UEMCON 2017: 145-149 - [c21]Kenichi Yoneda, Gary M. Weiss:
Mobile sensor-based biometrics using common daily activities. UEMCON 2017: 584-590 - 2016
- [c20]Gary M. Weiss, Jessica L. Timko, Catherine M. Gallagher, Kenichi Yoneda, Andrew J. Schreiber:
Smartwatch-based activity recognition: A machine learning approach. BHI 2016: 426-429 - [c19]Gary M. Weiss, Jeffrey W. Lockhart, Tony T. Pulickal, Paul T. McHugh, Isaac H. Ronan, Jessica L. Timko:
Actitracker: A Smartphone-Based Activity Recognition System for Improving Health and Well-Being. DSAA 2016: 682-688 - 2015
- [c18]Andrew H. Johnston, Gary M. Weiss:
Smartwatch-based biometric gait recognition. BTAS 2015: 1-6 - 2014
- [c17]Jeffrey W. Lockhart, Gary M. Weiss:
Limitations with activity recognition methodology & data sets. UbiComp Adjunct 2014: 747-756 - [c16]Jeffrey W. Lockhart, Gary M. Weiss:
The Benefits of Personalized Smartphone-Based Activity Recognition Models. SDM 2014: 614-622 - 2013
- [c15]Gary M. Weiss, Ashwin Nathan, J. B. Kropp, Jeffrey W. Lockhart:
WagTag: a dog collar accessory for monitoring canine activity levels. UbiComp (Adjunct Publication) 2013: 405-414 - 2012
- [c14]Gary M. Weiss, Jeffrey W. Lockhart:
A comparison of alternative client/server architectures for ubiquitous mobile sensor-based applications. UbiComp 2012: 721-724 - [c13]Jeffrey W. Lockhart, Tony T. Pulickal, Gary M. Weiss:
Applications of mobile activity recognition. UbiComp 2012: 1054-1058 - 2011
- [i1]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) - 2010
- [j9]Jennifer R. Kwapisz, Gary M. Weiss, Samuel Moore:
Activity recognition using cell phone accelerometers. SIGKDD Explor. 12(2): 74-82 (2010) - [c12]Jennifer R. Kwapisz, Gary M. Weiss, Samuel Moore:
Cell phone-based biometric identification. BTAS 2010: 1-7 - [p4]Gary M. Weiss:
Mining with Rare Cases. Data Mining and Knowledge Discovery Handbook 2010: 747-757 - [p3]Gary M. Weiss:
The Impact of Small Disjuncts on Classifier Learning. Data Mining 2010: 193-226 - [e1]Robert Stahlbock, Sven F. Crone, Mahmoud Abou-Nasr, Hamid R. Arabnia, Nikolaos Kourentzes, Philippe Lenca, Wolfram-Manfred Lippe, Gary M. Weiss:
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 [contents]
2000 – 2009
- 2009
- [c11]Gary M. Weiss:
Data Mining in the Real World: Experiences, Challenges, and Recommendations. DMIN 2009: 124-130 - [c10]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 - [c9]Ye Tian, Gary M. Weiss, D. Frank Hsu, Qiang Ma:
A Combinatorial Fusion Method for Feature Construction. DMIN 2009: 260-266 - [c8]Jack Chongjie Xue, Gary M. Weiss:
Quantification and semi-supervised classification methods for handling changes in class distribution. KDD 2009: 897-906 - [r2]Gary Weiss:
Data Mining in the Telecommunications Industry. Encyclopedia of Data Warehousing and Mining 2009: 486-491 - [r1]Tamraparni Dasu, Gary Weiss:
Mining Data Streams. Encyclopedia of Data Warehousing and Mining 2009: 1248-1256 - 2008
- [j8]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) - [j7]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) - 2007
- [c7]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 - 2006
- [j6]Gary M. Weiss, Ye Tian:
Maximizing classifier utility when training data is costly. SIGKDD Explor. 8(2): 31-38 (2006) - [j5]Bianca Zadrozny, Gary M. Weiss, Maytal Saar-Tsechansky:
UBDM 2006: Utility-Based Data Mining 2006 workshop report. SIGKDD Explor. 8(2): 98-101 (2006) - 2005
- [j4]Gary M. Weiss, Maytal Saar-Tsechansky, Bianca Zadrozny:
Report on UBDM-05: Workshop on Utility-Based Data Mining. SIGKDD Explor. 7(2): 145-147 (2005) - [p2]Gary M. Weiss:
Mining with Rare Cases. The Data Mining and Knowledge Discovery Handbook 2005: 765-776 - [p1]Gary M. Weiss:
Data Mining in Telecommunications. The Data Mining and Knowledge Discovery Handbook 2005: 1189-1201 - 2004
- [j3]Gary M. Weiss:
Mining with rarity: a unifying framework. SIGKDD Explor. 6(1): 7-19 (2004) - 2003
- [j2]Gary M. Weiss, Foster J. Provost:
Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction. J. Artif. Intell. Res. 19: 315-354 (2003) - 2000
- [c6]Gary M. Weiss, Haym Hirsh:
A Quantitative Study of Small Disjuncts. AAAI/IAAI 2000: 665-670
1990 – 1999
- 1998
- [j1]Gary M. Weiss, Johannes P. Ros:
Implementing Design Patterns with Object-Oriented Rules. J. Object Oriented Program. 11(7): 25-27, 35 (1998) - [c5]Gary M. Weiss, Johannes P. Ros, Anoop Singhal:
ANSWER: Network Monitoring Using Object-Oriented Rules. AAAI/IAAI 1998: 1087-1093 - [c4]Gary M. Weiss, Haym Hirsh:
The Problem with Noise and Small Disjuncts. ICML 1998: 574- - [c3]Gary M. Weiss, Haym Hirsh:
Learning to Predict Rare Events in Event Sequences. KDD 1998: 359-363 - 1996
- [c2]Anoop Singhal, Gary M. Weiss, Johannes P. Ros:
A model based reasoning approach to network monitoring. DART@CIKM 1996: 41-44 - 1995
- [c1]Gary M. Weiss:
Learning with Rare Cases and Small Disjuncts. ICML 1995: 558-565
Coauthor Index
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last updated on 2024-10-31 21:07 CET by the dblp team
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