We stand with Ukraine

We stand with Ukraine

Gary Weiss

Orcid: 0000-0001-5009-7101

Affiliations:

Fordham University, New York, NY, USA

According to our database¹, Gary Weiss authored at least 61 papers between 1995 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of two.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Links

Online presence:

on orcid.org
on ieeexplore.ieee.org

On csauthors.net:

Bibliography

2024

A Quantitative Machine Learning Approach to Evaluating Letters of Recommendation.

[BibT_eX]

[DOI]

,

,

,

,

,

Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

Introduction to the Minitrack on Educational Data Mining for Decision Making.

[BibT_eX]

[DOI]

,

Daniel D. Leeds

,

,

Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

Predicting GRE Scores from Application Materials in Test-Optional Admissions.

[BibT_eX]

[DOI]

,

,

,

,

,

Proceedings of the 17th International Conference on Educational Data Mining, 2024

GPT vs. Llama2: Which Comes Closer to Human Writing?

[BibT_eX]

[DOI]

Fernando Martinez

,

,

,

,

Alexander Borelli

,

Proceedings of the 17th International Conference on Educational Data Mining, 2024

The Construction and Analysis of Course Grades Across Public Universities.

[BibT_eX]

[DOI]

,

,

,

Daniel D. Leeds

Proceedings of the 17th International Conference on Educational Data Mining, 2024

2023

An Analysis of Grading Patterns in Undergraduate University Courses.

[BibT_eX]

[DOI]

,

Luisa A. L. Rosa

,

,

Daniel D. Leeds

Proceedings of the 47th IEEE Annual Computers, Software, and Applications Conference, 2023

2022

Generalized Sequential Pattern Mining of Undergraduate Courses.

[BibT_eX]

[DOI]

Daniel D. Leeds

,

,

,

,

,

Proceedings of the 15th International Conference on Educational Data Mining, 2022

The Impact of Semester Gaps on Student Grades.

[BibT_eX]

[DOI]

,

,

Daniel D. Leeds

Proceedings of the 15th International Conference on Educational Data Mining, 2022

Assessing Instructor Effectiveness Based on Future Student Performance.

[BibT_eX]

[DOI]

,

,

Michael Riad-Zaky

,

,

Daniel D. Leeds

Proceedings of the 15th International Conference on Educational Data Mining, 2022

2021

Identifying Hubs in Undergraduate Course Networks Based on Scaled Co-Enrollments: Extended Version.

[BibT_eX]

[DOI]

,

,

Karla Dominguez

,

Daniel D. Leeds

CoRR, 2021

Mining Course Groupings based on Academic Performance.

[BibT_eX]

Daniel D. Leeds

,

,

Proceedings of the 14th International Conference on Educational Data Mining, 2021

Measuring the Academic Impact of Course Sequencing using Student Grade Data.

[BibT_eX]

Tess Gutenbrunner

,

Daniel D. Leeds

,

,

Michael Riad-Zaky

,

Proceedings of the 14th International Conference on Educational Data Mining, 2021

Identifying Hubs in Undergraduate Course Networks Based on Scaled Co-Enrollments.

[BibT_eX]

,

,

Karla Dominguez

,

Daniel D. Leeds

Proceedings of the 14th International Conference on Educational Data Mining, 2021

2020

Event Detection Through Differential Pattern Mining in Cyber-Physical Systems.

[BibT_eX]

[DOI]

Md. Zakirul Alam Bhuiyan

,

,

,

Thaier Hayajneh

,

,

IEEE Trans. Big Data, 2020

A College Major Recommendation System.

[BibT_eX]

[DOI]

Samuel Alexander Stein

,

,

,

Daniel D. Leeds

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Predicting Student Performance in a Master's Program in Data Science using Admissions Data.

[BibT_eX]

[DOI]

,

,

,

Proceedings of the 13th International Conference on Educational Data Mining, 2020

2019

WISDM Smartphone and Smartwatch Activity and Biometrics Dataset.

[BibT_eX]

[DOI]

Dataset, October, 2019

Smartphone and Smartwatch-Based Biometrics Using Activities of Daily Living.

[BibT_eX]

[DOI]

,

,

Thaier Hayajneh

IEEE Access, 2019

An Overview of Wearable Computing.

[BibT_eX]

[DOI]

,

Md. Zakirul Alam Bhuiyan

Proceedings of the Mission-Oriented Sensor Networks and Systems: Art and Science, 2019

Mobile Target Tracking with Multiple Objectives in Wireless Sensor Networks.

[BibT_eX]

[DOI]

Md. Zakirul Alam Bhuiyan

,

,

,

Proceedings of the Mission-Oriented Sensor Networks and Systems: Art and Science, 2019

2018

Identification of Candidate Genes Responsible for Age-related Macular Degeneration using Microarray Data.

[BibT_eX]

[DOI]

,

,

Stuart M. Brown

Int. J. Serv. Sci. Manag. Eng. Technol., 2018

Cost-Sensitive Learning: Preface.

[BibT_eX]

[DOI]

,

,

,

,

Proceedings of the International Workshop on Cost-Sensitive Learning, 2018

2017

Mobile sensor-based biometrics using common daily activities.

[BibT_eX]

[DOI]

,

Proceedings of the 8th IEEE Annual Ubiquitous Computing, 2017

Smartwatch-based transcription biometrics.

[BibT_eX]

[DOI]

Francesco Ciuffo

,

Proceedings of the 8th IEEE Annual Ubiquitous Computing, 2017

Identifying sunni extremist propaganda with deep learning.

[BibT_eX]

[DOI]

Andrew H. Johnston

,

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Maintaining the Balance between Privacy and Data Integrity in Internet of Things.

[BibT_eX]

[DOI]

Md. Zakirul Alam Bhuiyan

,

,

Thaier Hayajneh

,

Proceedings of the 2017 International Conference on Management Engineering, 2017

2016

Actitracker: A Smartphone-Based Activity Recognition System for Improving Health and Well-Being.

[BibT_eX]

[DOI]

,

Jeffrey W. Lockhart

,

Tony T. Pulickal

,

,

,

Jessica L. Timko

Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

Smartwatch-based activity recognition: A machine learning approach.

[BibT_eX]

[DOI]

,

Jessica L. Timko

,

Catherine M. Gallagher

,

,

Andrew J. Schreiber

Proceedings of the 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics, 2016

2015

Smartwatch-based biometric gait recognition.

[BibT_eX]

[DOI]

Andrew H. Johnston

,

Proceedings of the IEEE 7th International Conference on Biometrics Theory, 2015

2014

The Benefits of Personalized Smartphone-Based Activity Recognition Models.

[BibT_eX]

[DOI]

Jeffrey W. Lockhart

,

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Limitations with activity recognition methodology & data sets.

[BibT_eX]

[DOI]

Jeffrey W. Lockhart

,

Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2014

2013

WagTag: a dog collar accessory for monitoring canine activity levels.

[BibT_eX]

[DOI]

,

,

,

Jeffrey W. Lockhart

Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2013

2012

A comparison of alternative client/server architectures for ubiquitous mobile sensor-based applications.

[BibT_eX]

[DOI]

,

Jeffrey W. Lockhart

Proceedings of the 2012 ACM Conference on Ubiquitous Computing, 2012

Applications of mobile activity recognition.

[BibT_eX]

[DOI]

Jeffrey W. Lockhart

,

Tony T. Pulickal

,

Proceedings of the 2012 ACM Conference on Ubiquitous Computing, 2012

2010

The Impact of Small Disjuncts on Classifier Learning.

[BibT_eX]

[DOI]

Proceedings of the Data Mining - Special Issue in Annals of Information Systems, 2010

Mining with Rare Cases.

[BibT_eX]

[DOI]

Proceedings of the Data Mining and Knowledge Discovery Handbook, 2nd ed., 2010

Activity recognition using cell phone accelerometers.

[BibT_eX]

[DOI]

Jennifer R. Kwapisz

,

,

SIGKDD Explor., 2010

Cell phone-based biometric identification.

[BibT_eX]

[DOI]

Jennifer R. Kwapisz

,

,

Proceedings of the Fourth IEEE International Conference on Biometrics: Theory Applications and Systems, 2010

2009

Data Mining in the Telecommunications Industry.

[BibT_eX]

[DOI]

Proceedings of the Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes), 2009

Mining Data Streams.

[BibT_eX]

[DOI]

Tamraparni Dasu

,

Proceedings of the Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes), 2009

Quantification and semi-supervised classification methods for handling changes in class distribution.

[BibT_eX]

[DOI]

Jack Chongjie Xue

,

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Data Mining in the Real World: Experiences, Challenges, and Recommendations.

[BibT_eX]

Proceedings of The 2009 International Conference on Data Mining, 2009

A Combinatorial Fusion Method for Feature Construction.

[BibT_eX]

,

,

,

Proceedings of The 2009 International Conference on Data Mining, 2009

Are Decision Trees Always Greener on the Open (Source) Side of the Fence?

[BibT_eX]

,

Daniel D'Addario

,

James Kurinskas

,

Proceedings of The 2009 International Conference on Data Mining, 2009

2008

Guest editorial: special issue on utility-based data mining.

[BibT_eX]

[DOI]

,

Bianca Zadrozny

,

Maytal Saar-Tsechansky

Data Min. Knowl. Discov., 2008

Maximizing classifier utility when there are data acquisition and modeling costs.

[BibT_eX]

[DOI]

,

Data Min. Knowl. Discov., 2008

2007

Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?

[BibT_eX]

,

,

Proceedings of the 2007 International Conference on Data Mining, 2007

2006

UBDM 2006: Utility-Based Data Mining 2006 workshop report.

[BibT_eX]

[DOI]

Bianca Zadrozny

,

,

Maytal Saar-Tsechansky

SIGKDD Explor., 2006

Maximizing classifier utility when training data is costly.

[BibT_eX]

[DOI]

,

SIGKDD Explor., 2006

2005

Report on UBDM-05: Workshop on Utility-Based Data Mining.

[BibT_eX]

[DOI]

,

Maytal Saar-Tsechansky

,

Bianca Zadrozny

SIGKDD Explor., 2005

Data Mining in Telecommunications.

[BibT_eX]

Proceedings of the Data Mining and Knowledge Discovery Handbook., 2005

Mining with Rare Cases.

[BibT_eX]

Proceedings of the Data Mining and Knowledge Discovery Handbook., 2005

2004

Mining with rarity: a unifying framework.

[BibT_eX]

[DOI]

SIGKDD Explor., 2004

2003

Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction.

[BibT_eX]

[DOI]

,

Foster J. Provost

J. Artif. Intell. Res., 2003

2000

A Quantitative Study of Small Disjuncts.

[BibT_eX]

[DOI]

,

Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

1998

Implementing Design Patterns with Object-Oriented Rules.

[BibT_eX]

,

Johannes P. Ros

J. Object Oriented Program., 1998

Learning to Predict Rare Events in Event Sequences.

[BibT_eX]

[DOI]

,

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

The Problem with Noise and Small Disjuncts.

[BibT_eX]

,

Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

ANSWER: Network Monitoring Using Object-Oriented Rules.

[BibT_eX]

[DOI]

,

Johannes P. Ros

,

Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

1996

A model based reasoning approach to network monitoring.

[BibT_eX]

[DOI]

,

,

Johannes P. Ros

Proceedings of the Workshop on Databases - Active and Real-Time, 1996

1995

Learning with Rare Cases and Small Disjuncts.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 1995

Loading...