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Publications (by Type)

You may also view the publications by: year, area, or top-10 most popular. Click on the title to view the publication in pdf format. The top-10 most popular papers are tagged (in red) with the approximate number of citations and clicking on the tag will bring up the list of citing papers in google scholar. You can also view my Google Scholar Profile.

Journal Articles

  1. Yijun Zhao, Zhengxin Qi, John Grossi, and Gary M. Weiss (2023). Gender and Culture Bias in Letters of Recommendation for Computer Science and Data Science Masters Programs, Scientific Reports, 13:14367, Sept 2023. https://doi.org/10.1038/s41598-023-41564-w
  2. Yijun Zhao, Xiaoyu Chen, Haoran Xue, and Gary M. Weiss (2023). A machine learning approach to graduate admissions and the role of letters of recommendation. PLoS ONE, 18:10:e0291107. https://doi.org/10.1371/journal.pone.0291107
  3. Gary M. Weiss, Kenichi Yoneda, and Thaier Hayajneh (2019). Smartphone and Smartwatch-Based Biometrics Using Activities of Daily Living. IEEE Access, 7:133190-133202, Sept. 2019. 205 citations
  4. Abdullah Alhayajneh, Alessandro N. Baccarini, Gary M. Weiss, Thaier Hayajneh, and Aydin Farajidavar (2018). Biometric Authentication and Verification for Medical Cyber Physical Systems, Electronics, 7(12), 436.
  5. Yuhan Hao, Gary M. Weiss, and Stuart Brown (2018). Identification of Candidate Genes Responsible for Age-related Macular Degeneration using Microarray Data, International Journal of Service Science, Management, Engineering, and Technology, 9(2):33-60.
  6. Md Zakirul Alam Bhuiyan, Jie Wu, Gary M. Weiss, Thaier Hayajneh, Tian Wang, and Guojun Wang (2017). Event Detection through Differential Pattern Mining in Cyber-Physical Systems, IEEE Transactions on Big Data.
  7. Gary M. Weiss (2013). Smartphone Sensor Mining Research: Successes and Lessons, CUR Quarterly, 34(2):17-21.
  8. Gary M. Weiss (2010). The Impact of Small Disjuncts on Classifier Learning. Annals of Information Systems, 8:193-226.
  9. Gary M. Weiss and Ye Tian (2008). Maximizing Classifier Utility when there are Data Acquisition and Modeling Costs. Data Mining and Knowledge Discovery, 17(2): 253-282. (abstract)
  10. Gary M. Weiss and Foster Provost (2003). Learning when Training Data are Costly: The Effect of Class Distribution on Tree Induction, Journal of Artificial Intelligence Research, 19:315-354.  1195 citations
  11. Gary. M. Weiss and Johannes P. Ros (1998). Implementing Design Patterns with Object-Oriented Rules, Journal of Object-Oriented Programming, 11(7): 25-35, SIGS Publications Inc, New York.

Academic Magazine Research Articles

  1. Jennifer R. Kwapisz, Gary M. Weiss and Samuel A. Moore (2010). Activity Recognition using Cell Phone Accelerometers, ACM SIGKDD Explorations, 12(2):74-82. 3031 citations
  2. Gary M. Weiss and Ye Tian (2006). Maximizing Classifier Utility when Training Data is Costly, ACM SIGKDD Explorations, 8(2):31-38.
  3. Gary M. Weiss (2004). Mining with Rarity: A Unifying Framework, ACM SIGKDD Explorations, 6(1):7-19. 1858 citations

Books

  1. Damian M. Lyons, Christina Papadakis-Kanaris, Gary M. Weiss, Arthur G. Werschulz (2012). Fundamentals of Discrete Structures 2nd edition, Pearson Learning Solutions. Available at Amazon.

Book Chapters

  1. Faiza Khan, Gary M. Weiss, and Daniel D. Leeds (2021). Predicting the Academic Performance of Undergraduate Computer Science Students Using Data Mining. In: Arabnia H.R., Deligiannidis L., Tinetti F.G., Tran QN. (eds) Advances in Software Engineering, Education, and e-Learning. Transactions on Computational Science and Computational Intelligence. Springer, Cham, 303-317.
  2. Yifan Ren, and Gary M. Weiss (2021). A Comparison of Important Features for Predicting Polish and Chinese Corporate Bankruptcies. In Advances in Data Science and Information Engineering. Transactions on Computational Science and Computational Intelligence. Springer, Cham, 187-198. https://doi.org/10.1007/978-3-030-71704-9_12
  3. Gary M. Weiss and Md Zakirul Alam Bhuiyan (2019). An Overview of Wearable Computing. In H.M. Ammari (ed.), Mission-Oriented Sensor Networks and Systems:Art and Science, Studies in Systems, Decision and Control, vol. 164, Springer, 313-349.
  4. Md Zakirul Alam Bhuiyan, Gary M. Weiss, Tian Wang, Geyong Min (2019). Mobile Target Tracking with Multiple Objectives in Wireless Sensor Networks. In H.M. Ammari (ed.), Mission-Oriented Sensor Networks and Systems:Art and Science, Studies in Systems, Decision, and Control, vol. 163, Springer, 437-495.
  5. Yuhan Hao, Gary M. Weiss, and Stuart M. Brown (2019). Identification of Candidate Genes Responsible for Age-Related Macular Degeneration Using Microarray Data, Biotechnology: Concepts, Methodologies, Tools, and Applications, Chapter 38, IGI Global, 969-1001. (reprint of previous work)
    doi:10.4018/978-1-5225-8903-7.ch038
  6. Mahmoud Abou-Nasr, Stefan Lessman, Robert Stahlbock, and Gary M. Weiss (2015). Introduction. In Real World Data Mining Applications (special issue of Annals of Information Systems, Vol. 17), Springer, 1-14.
  7. Gary M. Weiss (2013). Foundations of Imbalanced Learning (preprint). In H. He and Y. Ma (eds.), Imbalanced Learning: Foundations, Algorithms and Applications, Wiley-IEEE Press, 13-41. Preprint posted by permission of publisher. Book available for purchase [Amazon, Wiley].
  8. Gary M. Weiss and Brian Davison (2010). Data Mining. In H. Bidgoli (ed.), Handbook of Technology Management, John Wiley and Sons, Volume 2, 542-555.
  9. Gary M. Weiss (2008). Data Mining in the Telecommunications Industry. In J. Wang (ed.), Encyclopedia of Data Warehousing and Mining, Second Edition, Information Science Publishing, Volume 1, 486-491. Copyright 2008, IGI Global, www.igi-global.com. Posted by permission of the publisher.
  10. Tamraparni Dasu and Gary M. Weiss (2008). Mining Data Streams. In J. Wang (ed.), Encyclopedia of Data Warehousing and Mining, Second Edition, Information Science Publishing, Volume 3, 1248-1256. Copyright 2008, IGI Global, www.igi-global.com. Posted by permission of the publisher.
  11. Gary M. Weiss (2005). Mining with Rare Cases. In O. Maimon and L. Rokach(eds.), Data Mining and Knowledge Discovery Handbook: A Complete Guide for Practitioners and Researchers, Kluwer Academic Publishers, 747-757.
  12. Gary M. Weiss (2005). Data Mining in Telecommunications. In O. Maimon and L. Rokach(eds.), Data Mining and Knowledge Discovery Handbook: A Complete Guide for Practitioners and Researchers, Kluwer Academic Publishers, 1189-1201.
  13. Gary M. Weiss (2002). Predicting Telecommunication Equipment Failures from Sequences of Network Alarms. In W. Kloesgen and J. Zytkow (eds.), Handbook of Knowledge Discovery and Data Mining, Oxford University Press, 891-896.
  14. Gary M. Weiss John Eddy, & Sholom Weiss (1998). Intelligent Telecommunication Technologies, Knowledge-based Intelligent Techniques (chapter 8), L. C. Jain, editor, CRC Press, 249-275.

Conference Papers

  1. Yijun Zhao, Tianyu Wang, Douglas Mensah, Ellise Parnoff, Siyi He, and Gary M. Weiss (2004). A Quantitative Machine Learning Approach to Evaluating Letters of Recommendation. Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS), Hawaii, USA, January 3-6, 1276-1284.
  2. Gary M. Weiss, Luisa A. L. Rosa, Hyun Jeong and Daniel D. Leeds (2023). An Analysis of Grading Patterns in Undergraduate University Courses. Proceedings of the 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC), IEEE, Torino, Italy, June 26-30, 310-315 (official version).
  3. Gary M. Weiss, Erik Brown, Michael Riad-Zaky, Ruby Iannone, and Daniel D. Leeds (2022). Assessing Instructor Effectiveness Based on Future Student Performance. Proceedings of The 15th International Conference on Educational Data Mining (EDM22), International Educational Data Mining Society, Durham, UK, July 24-27, 616-620.
  4. Gary M. Weiss, Joseph Denham, and Daniel D. Leeds (2022). The Impact of Semester Gaps on Student Grades. Proceedings of The 15th International Conference on Educational Data Mining (EDM22), International Educational Data Mining Society, Durham, UK, July 24-27, 612-615.
  5. Daniel D. Leeds, Cody Chen, Yijun Zhao, Fiza Metla, James Guest, and Gary M. Weiss (2022). Generalized Sequential Pattern Mining of Undergraduate Courses, Proceedings of The 15th International Conference on Educational Data Mining (EDM22), International Educational Data Mining Society, Durham, UK, July 24-27, 629-633.
  6. Gary M. Weiss, Nam Nguyen, Karla Dominguez and Daniel D. Leeds (2021). Identifying Hubs in Undergraduate Course Networks Based on Scaled Co-Enrollments. Proceedings of The 14th International Conference on Educational Data Mining (EDM21), International Educational Data Mining Society, Paris, France, 809-813.
  7. Tess Gutenbrunner, Daniel D. Leeds, Spencer Ross, Michael Riad-Zaky, and Gary M. Weiss (2021). Measuring the Academic Impact of Course Sequencing using Student Grade Data. Proceedings of The 14th International Conference on Educational Data Mining (EDM21), International Educational Data Mining Society, Paris, France, 799-803.
  8. Daniel D. Leeds, Tianyi Zhang and Gary M. Weiss (2021). Mining Course Groupings using Academic Performance. Proceedings of The 14th International Conference on Educational Data Mining (EDM21), International Educational Data Mining Society, Paris, France, 804-808.
  9. Samuel A. Stein, Gary M. Weiss, Yiwen Chen, and Daniel D. Leeds (2020). A College Major Recommendation System. Proceedings of the Fourteenth ACM Conference on Recommender Systems (RECSYS 20), 640-644, September 2020.
  10. Yijun Zhao, Qiangwen Xu, Ming Chen, and Gary M. Weiss (2020). Predicting Student Performance in a Master of Data Science Program using Admissions Data. Proceedings of the 13th International Conference on Educational Data Mining (EDM 2020), 325-333.
  11. Ray M. Tischio, and Gary M. Weiss (2019). Identifying Classification Algorithms Most Suitable for Imbalanced Data, Proceedings of the 15th International Conference on Data Science, 106-111, Las Vegas, NV.
  12. Movses Musaelian, Md Zakirul Alam Bhuiyan, Gary M. Weiss, Tian Wang, Aliuz Zaman, and Thaier Hayajneh (2019). Data Science and Security in Digital Governance Aspects and an Elastic Bus Transportation Scheme, Proceedings of the 15th International Conference on Data Science, 84-89, Las Vegas, NV.
  13. Xian Lai, and Gary M. Weiss (2018). RNN as a Multivariate Arrival Process Model: Modeling and Predicting Taxi Trips, Proceedings of the 14th International Conference on Data Science, Las Vegas, NV, 105-111.
  14. Emi N. Harry, and Gary M. Weiss (2018). Assessment of Minorities Access to Finance, Proceedings of the 14th International Conference on Data Science, Las Vegas, NV, 123-129.
  15. Andrew H. Johnston, and Gary M. Weiss (2017). Identifying Sunni Extremist Propaganda with Deep Learning, Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, Honolulu, Hawaii.
  16. Kenichi Yoneda and Gary M. Weiss (2017). Mobile Sensor-based Biometrics using Common Daily Activities, Proceedings of the 8th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference, New York, NY, 584-590.
  17. Francesco Ciuffo and Gary M. Weiss (2017). Smartwatch-Based Transcription Biometrics, Proceedings of the 8th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference, New York, NY, 145-149.
  18. Md Zakirul Alam Bhuiyan, Tian Wang, Thaier Hayajneh, and Gary M. Weiss (2017). Maintaining the Balance between Privacy and Data Integrity in Internet of Things, Proceedings of the 2017 International Conference on Management Engineering, Software Engineering and Service Sciences (ICMSS), Wuhan, China, 177-182.
  19. Gary M. Weiss, Jeffrey W. Lockhart, Tony T. Pulickal, Paul T. McHugh, Isaac H. Ronan, and Jessica L. Timko (2016). Actitracker: A Smartphone-based Activity Recognition System for Improving Health and Well-Being, Proceedings of the IEEE 3rd IEEE International Conference on Data Science and Advanced Analytics (DSAA), Montreal, Canada.
  20. Yuhan Hao and Gary M. Weiss (2016). Gene Selection from Microarray Data for Age-related Macular Degeneration by Data Mining, Proceedings of the 2016 International Conference on Data Mining (DMIN 2016), Las Vegas, NV, 125 - 129.
  21. Gary M. Weiss, Jessica L. Timko, Catherine M. Gallagher, Kenichi Yoneda, and Andrew J. Schreiber (2016). Smartwatch-based Activity Recognition: A Machine Learning Approach, Proceedings of the 2016 IEEE International Conference on Biomedical and Health Informatics (BHI 2016), Las Vegas, NV, 426-429. 220 citations
  22. Andrew H. Johnston and Gary M. Weiss (2015). Smartwatch-Based Gait Recognition, Proceedings of the Seventh IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS 2015), Washington DC.
  23. Gary M. Weiss and Alexander Battistin (2014). Generating Well-Behaved Learning Curves: An Empirical Study, Proceedings of the Tenth International Conference on Data Mining, Las Vegas, NV, 210-213.
  24. Jeffrey W. Lockhart and Gary M. Weiss (2014). The Benefits of Personalized Models for Smartphone-Based Activity Recognition, Proceedings of the 2014 SIAM International Conference on Data Mining, Society for Industrial and Applied Mathematics, Philadelphia, PA, 614-622.
  25. Jennifer R. Kwapisz, Gary M. Weiss and Samuel A. Moore (2010). Cell Phone-Based Biometric Identification, Proceedings of the IEEE Fourth International Conference on Biometrics: Theory, Applications and Systems (BTAS-10), Washington DC. 384 citations
  26. Jack Chongjie Xue and Gary M. Weiss (2009). Quantification and Semi-Supervised Classification Methods for Handling Changes in Class Distribution, Proceedings of the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-09), ACM Press, 897-905.
  27. Ye Tian, Gary M. Weiss, D. Frank Hsu and Qiang Ma (2009). A Combinatorial Fusion Method for Feature Construction, Proceedings of the 2009 International Conference on Data Mining, CSREA Press, 260-266.
  28. Gary M. Weiss (2009). Data Mining in the Real World: Experiences, Challenges, and Recommendations, Proceedings of the 2009 International Conference on Data Mining, CSREA Press, 124-130.
  29. Samuel Moore, Daniel D'Addario, James Kurinskas, and Gary M. Weiss (2009). Are Decision Trees Always Greener on the Open (Source) Side of the Fence?, Proceedings of the 2009 International Conference on Data Mining, CSREA Press, 185-188.
  30. Gary M. Weiss, Kate McCarthy and Bibi Zabar (2007). Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?, Proceedings of the 2007 International Conference on Data Mining, CSREA Press, 35-41. 365 citations
  31. Gary M. Weiss and Haym Hirsh (2000). A Quantitative Study of Small Disjuncts. Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), AAAI Press, Menlo Park, CA, 665-670. An expanded version is also available.
  32. Gary M. Weiss (1999). Timeweaver: a Genetic Algorithm for Identifying Predictive Patterns in Sequences of Events. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-99), Morgan Kaufmann, San Francisco, CA, 718-725.  
  33. Gary M. Weiss and Haym Hirsh (1998). Learning to Predict Rare Events in Event Sequences, Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), AAAI Press, Menlo Park, CA, 359-363.   377 citations
  34. Gary M. Weiss, Johannes P. Ros, Anoop Singhal (1998). ANSWER: Network Monitoring Using Object-Oriented Rules, Proceedings of the Tenth Conference on Innovative Applications of Artificial Intelligence (IAAI-98), AAAI Press, Menlo Park, CA, 1087-1093.
  35. Gary M. Weiss and Haym Hirsh (1998). The Problem with Noise and Small Disjuncts, Proceedings of the Fifteenth International Conference on Machine Learning (ICML-98). Morgan Kaufmann, San Francisco, CA, 574-578.
  36. Dan Dvorak, Anil Mishra, Johannes Ros, Gary M. Weiss & Diane Litman (1996). R++: Using Rules in Object-Oriented Designs, in Addendum Object-Oriented Programming Systems, Languages and Applications (OOPSLA) San Jose, CA.
  37. Gary M. Weiss (1995). Learning with Rare Cases and Small Disjuncts, Proceedings of the Twelfth International Conference on Machine Learning, Lake Tahoe, California, 558-565.  

Edited Works

  1. Robert Stahlbock, Gary M. Weiss, Mahmoud Abou-Nasr, Cheng-Ying Yang, Hamid R. Arabnia, Leonidas Deligiannidis, editors, 2021. Advances in Data Science and Information Engineering: Proceedings from ICDATA 2020 and IKE 2020. Advances in Data Science and Information Engineering, Springer, Cham.
  2. Robert Stahlbock, Gary M. Weiss, and Mahmoud Abou-Nasr, editors, 2019. Proceedings of the 20l9 International Conference on Data Science (ICDATA '19), CSREA Press, Las Vegas, NV, July 2019.
  3. Luís Torgo, Stan Matwin, Gary M. Weiss, Nuno Moniz, Paula Branco, editors, 2018. Proceedings of The International Workshop on Cost-Sensitive Learning, published as Proceedings of Machine Learning Research (PMLR): Vol. 88, May 5, 2018.
  4. Peter Geczy, Robert Stahlbock, Gary M. Weiss, Mahmoud Abou-Nasr, David Baglee, and Chris Bowerman, editors (2018). Special issue on Back Stage Techniques in Servitization, International Journal of Service Science, Management, Engineering, and Technology, 9(2).
  5. Robert Stahlbock, Gary M. Weiss, and Mahmoud Abou-Nasr, editors (2018). Proceedings of the 20l8 International Conference on Data Science (ICDATA '18), CSREA Press, Las Vegas, NV, July 2018.
  6. Robert Stahlbock, Mahmoud Abou-Nasr, and Gary M. Weiss, editors (2017). Proceedings of the 20l7 International Conference on Data Mining (DMIN '17), CSREA Press, Las Vegas, NV, July 2017.
  7. Robert Stahlbock and Gary M. Weiss, editors (2016). Proceedings of the 20l6 International Conference on Data Mining (DMIN '16), CSREA Press, Las Vegas, NV, July 2016.
  8. Robert Stahlbock and Gary M. Weiss, editors (2015). Proceedings of the 20l5 International Conference on Data Mining (DMIN '15), CSREA Press, Las Vegas, NV, July 2015.
  9. Mahmoud Abou-Nasr, Stefan Lessman, Robert Stahlbock, and Gary M. Weiss, editors (2015). Real World Data Mining Applications. Annals of Information Systems, Vol. 17, Springer. Available from Springer.
  10. Robert Stahlbock and Gary M. Weiss, editors (2014). Proceedings of the 20l4 International Conference on Data Mining (DMIN '14), CSREA Press, Las Vegas, NV, July 2014.
  11. Robert Stahlbock and Gary M. Weiss, editors (2013). Proceedings of the 2013 International Conference on Data Mining (DMIN '13), CSREA Press, Las Vegas, NV, July 2013.
  12. Robert Stahlbock and Gary M. Weiss, editors (2012). Proceedings of the 2012 International Conference on Data Mining (DMIN '12), CSREA Press, Las Vegas, NV, July 2012.
  13. Robert Stahlbock editor, Mahmoud Abou-Nasr, Hamid Arabnia, Nikolas Kourentzes, Philippe Lenca, Wolfram-M. Lippe, Gary M. Weiss assoc. editors (2011). Proceedings of the 2011 International Conference on Data Mining (DMIN '11), CSREA Press, Las Vegas, NV, July 2011. (TOC)
  14. Robert Stahlbock, Sven Crone editors, Mahmoud Abou-Nasr, Hamid Arabnia, Nikolas Kourentzes, Philippe Lenca, Wolfram-M. Lippe, Gary M. Weiss assoc. editors (2010). Proceedings of the 2010 International Conference on Data Mining (DMIN '10), CSREA Press, Las Vegas, NV, July 2010.
  15. Robert Stahlbock, Sven Crone, Stefan Lessmann, editors, Mahmoud Abou-Nasr, Hamid Arabnia, Philippe Lenca, Yanjun Li, Wolfram-M. Lippe, Anthony Scime, Gary M. Weiss assoc. editors (2009). Proceedings of the 2009 International Conference on Data Mining (DMIN '09), CSREA Press, Las Vegas, NV, July 2009.
  16. Gary M. Weiss, Maytal Saar-Tsechansky and Bianca Zadrozny (2008). Special Issue on Utility-Based Data Mining (editors), Data Mining and Knowledge Discovery, 17(2).
  17. Robert Stahlbock, Sven Crone, Stefan Lessmann, editors, Gary Weiss, Hamid Arabnia, Philippe Lenca, Wolfram-M. Lippe, assoc. editors (2008). Proceedings of the 2008 International Conference on Data Mining (DMIN '08), Volumes I & II. CSREA Press, Las Vegas, NV, July 2008.
  18. Bianca Zadrozny, Gary. M. Weiss and Maytal Saar-Tsechansky (2006). Proceedings of the Second International Workshop on Utility-Based Data Mining (editors). ACM Press, Philadelphia, PA, August 2006.
  19. Gary M. Weiss, Maytal Saar-Tsechansky and Bianca Zadrozny (2005). Proceedings of the First International Workshop on Utility-Based Data Mining (editors). ACM Press, Chicago, IL, August 2005.

Columns, Editorials and Reports

  1. Gary M. Weiss (2013). Your Smartphone Knows You Better Than You Know Yourself. Inside Science, January 4, 2013.
  2. Gary M. Weiss, Bianca Zadrozny, and Maytal Sar-Tsechansky (2008). Guest editorial: special issue on utility-based data mining. Data Mining and Knowledge Discovery, 17(2): 129-135.
  3. Bianca Zadrozny, Gary. M. Weiss and Maytal Saar-Tsechansky (2006). UBDM 2006: Utility-Based Data Mining 2006 Workshop Report. ACM SIGKDD Explorations, 8(2), ACM Press, December 2006.
  4. Gary. M. Weiss, Maytal Saar-Tsechansky and Bianca Zadrozny (2005). Report on UBDM-05: Workshop on Utility-Based Data Mining. ACM SIGKDD Explorations, 7(2):145-147, ACM Press, December 2005.

Workshop Papers

  1. Jeffrey W. Lockhart and Gary M. Weiss (2014). Limitations with Activity Recognition Methodolgy & Data Sets, Proceedings of the 2014 ACM Conference on Ubiquitous Computing Adjunct Publication (2nd International Workshop on Human Activity Sensing Corpus and its Application), Seattle, WA, 747-756.
  2. Gary M. Weiss, Ashwin Nathan, JB Kropp, and Jeffrey W. Lockhart (2013). WagTag™: A Dog Collar Accessory for Monitoring Canine Activity Levels, Proceedings of the ACM UbiComp International Atelier on Smart Garments and Accessories, ACM Press, Zurich, Switzerland, 405-413.
  3. Gary M. Weiss and Jeffrey W. Lockhart (2012). A Comparison of Alternative Client/Server Architectures for Ubiquitous Mobile Sensor-Based Applications, Proceedings of the ACM UbiComp 1st International Workshop on Ubiquitous Mobile Instrumentation, Pittsburgh, PA.
  4. Jeffrey W. Lockhart, Tony Pulickal, and Gary M. Weiss (2012). Applications of Mobile Activity Recognition, Proceedings of the ACM UbiComp International Workshop on Situation, Activity, and Goal Awareness, Pittsburgh, PA.
  5. Gary M. Weiss and Jeffrey W. Lockhart (2012). The Impact of Personalization on Smartphone-Based Activity Recognition, Papers from the AAAI-12 Workshop on Activity Context Representation: Techniques and Languages, AAAI Technical Report WS-12-05, Toronto, Canada, 98-104. 233 citations
  6. Gary M. Weiss and Jeffrey W. Lockhart (2011). Identifying User Traits by Mining Smart Phone Accelerometer Data, Proceedings of the Fifth International Workshop on Knowledge Discovery from Sensor Data (at KDD-11), San Diego, CA, 61-69.
  7. Jeffrey W. Lockhart, Gary M. Weiss, Jack C. Xue, Shaun T. Gallagher, Andrew B. Grosner, and Tony T. Pulickal (2011) Design Considerations for the WISDM Smart Phone-Based Sensor Mining Architecture, Proceedings of the Fifth International Workshop on Knowledge Discovery from Sensor Data (at KDD-11), San Diego, CA, 25-33.
  8. Jennifer R. Kwapisz, Gary M. Weiss and Samuel A. Moore (2010). Activity Recognition using Cell Phone Accelerometers, Proceedings of the Fourth International Workshop on Knowledge Discovery from Sensor Data (at KDD-10), Washington DC, 10-18.
  9. Ye Tian, Gary M. Weiss and Qiang Ma (2007). A Semi-Supervised Approach for Web Spam Detection using Combinatorial Feature-Fusion, Proceedings of the ECML/PKDD 2007 Graph Labelling Workshop and Web Spam Challenge, 16-23.
  10. Ye Tian, Gary M. Weiss, D. Frank Hsu, and Qiang Ma (2007). A Combinatorial Fusion Method for Feature Mining, Proceedings of the First International Workshop on Mining Multiple Information Sources (at KDD-07), ACM Press, 6-13.
  11. Gary. M. Weiss and Ye Tian (2006). Maximizing Classifier Utility when Training Data is Costly, Proceedings of the Second International Workshop on Utility-Based Data Mining (at KDD-06), Philadelphia, PA, ACM Press, 3-11.
  12. Michelle Ciraco, Michael Rogalewski and Gary. M. Weiss (2005). Improving Classifier Utility by Altering the Misclassification Cost Ratio, Proceedings of the First International Workshop on Utility-Based Data Mining (at KDD-05), ACM Press, 46-52.
  13. Kate McCarthy, Bibi Zabar and Gary. M. Weiss (2005). Does Cost-Sensitive Learning Beat Sampling for Classifying Rare Classes?, Proceedings of the First International Workshop on Utility-Based Data Mining (at KDD-05), ACM Press, 69-75. 227 citations
  14. Gary M. Weiss and Haym Hirsh (2000). Learning to Predict Extremely Rare Events. Papers from the AAAI Workshop on Learning from Imbalanced Data Sets, Technical Report WS-00-05, AAAI Press, Menlo Park, CA, 64-68.
  15. Gary M. Weiss (1999). Mining Predictive Patterns in Sequences of Events. Presented at the 1999 AAAI/GECCO Workshop on Data Mining with Evolutionary Algorithms: Research Directions.
  16. Gary M. Weiss and Haym Hirsh (1998). Event Prediction: Learning from Ambiguous Examples. Presented at the 1998 Neural Information Processing Systems (NIPS) Workshop on Learning from Ambiguous and Complex Examples.
  17. Gary M. Weiss and Haym Hirsh (1998). Learning to Predict Rare Events in Categorical Time-Series Data, Papers from the AAAI Workshop on Predicting the Future: AI Approaches to Time-Series Problems, Technical Report WS-98-07, AAAI Press, Menlo Park, CA, 83-90.
  18. Anoop Singhal, Gary M. Weiss and Johannes Ros (1996). A Model Based Reasoning Approach to Network Monitoring, Proceedings of the ACM Workshop of Databases for Active and Real Time Systems (DART) Rockville, Maryland, 41-44.

Ph.D. Disseration

  1. Gary M. Weiss (2003). The Effect of Small Disjuncts and Class Distribution on Decision Tree Learning, Ph.D. Dissertation, Department of Computer Science, Rutgers University, New Brunswick, New Jersey, May 2003. (167 pages, 667 KB).