Moninder Singh

According to our database, Moninder Singh authored at least 66 papers between 1993 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Reasoning about concepts with LLMs: Inconsistencies abound.

Rosario Uceda-Sosa, Karthikeyan Natesan Ramamurthy, Maria Chang, Moninder Singh

CoRR, 2024

Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations.

Swapnaja Achintalwar, Ioana Baldini, Djallel Bouneffouf, Joan Byamugisha, Maria Chang, Pierre L. Dognin, Eitan Farchi, Ndivhuwo Makondo, Aleksandra Mojsilovic, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Inkit Padhi, Orna Raz, Jesus Rios, Prasanna Sattigeri, Moninder Singh, Siphiwe Thwala, Rosario A. Uceda-Sosa, Kush R. Varshney

CoRR, 2024

Ranking Large Language Models without Ground Truth.

Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy

Proceedings of the Findings of the Association for Computational Linguistics, 2024

SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models.

Manish Nagireddy, Lamogha Chiazor, Moninder Singh, Ioana Baldini

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions.

Manish Nagireddy, Moninder Singh, Samuel C. Hoffman, Evaline Ju, Karthikeyan Natesan Ramamurthy, Kush R. Varshney

CoRR, 2023

2022

On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach.

Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney, Elizabeth Daly, Moninder Singh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Write It Like You See It: Detectable Differences in Clinical Notes by Race Lead to Differential Model Recommendations.

Hammaad Adam, Ming-Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

Your fairness may vary: Pretrained language model fairness in toxic text classification.

Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh, Mikhail Yurochkin

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

AI Explainability 360: Impact and Design.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Ground-Truth, Whose Truth? - Examining the Challenges with Annotating Toxic Text Datasets.

Kofi Arhin, Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh

CoRR, 2021

An Empirical Study of Accuracy, Fairness, Explainability, Distributional Robustness, and Adversarial Robustness.

Moninder Singh, Gevorg Ghalachyan, Kush R. Varshney, Reginald E. Bryant

CoRR, 2021

Your fairness may vary: Group fairness of pretrained language models in toxic text classification.

Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Mikhail Yurochkin, Moninder Singh

CoRR, 2021

AI Explainability 360 Toolkit.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

Introduction to AI Fairness.

Yunfeng Zhang, Rachel K. E. Bellamy, Q. Vera Liao, Moninder Singh

Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Anomaly Attribution with Likelihood Compensation.

Tsuyoshi Idé, Amit Dhurandhar, Jirí Navrátil, Moninder Singh, Naoki Abe

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

J. Mach. Learn. Res., 2020

AI explainability 360: hands-on tutorial.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

Proceedings of the FAT* '20: Conference on Fairness, 2020

Introduction to Explainable AI.

Q. Vera Liao, Moninder Singh, Yunfeng Zhang, Rachel K. E. Bellamy

Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020

2019

Think Your Artificial Intelligence Software Is Fair? Think Again.

Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang

IEEE Softw., 2019

Teaching AI agents ethical values using reinforcement learning and policy orchestration.

Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi

IBM J. Res. Dev., 2019

AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias.

Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang

IBM J. Res. Dev., 2019

Understanding racial bias in health using the Medical Expenditure Panel Survey data.

Moninder Singh, Karthikeyan Natesan Ramamurthy

CoRR, 2019

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

CoRR, 2019

2018

Estimating Fungibility Between Skills by Combining Skill Similarities Obtained from Multiple Data Sources.

Shrihari Vasudevan, Moninder Singh, Joydeep Mondal, Michael Peran, Benjamin Zweig, Brian Johnston, Rachel Rosenfeld

Data Sci. Eng., 2018

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias.

Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang

CoRR, 2018

Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration.

Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi

CoRR, 2018

Assessing National Development Plans for Alignment With Sustainable Development Goals via Semantic Search.

Jonathan Galsurkar, Moninder Singh, Lingfei Wu, Aditya Vempaty, Mikhail Sushkov, Devika Iyer, Serge Kapto, Kush R. Varshney

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Effectiveness of peer detailing in a diarrhea program in Nigeria.

Yumeng Tao, Debarun Bhattacharjya, Aliza R. Heching, Aditya Vempaty, Moninder Singh, Felix Lam, Jan Houdek, M. Abubakar, Abdulwahab Alharbi, T. Braimoh, N. Ihebuzor, Aleksandra Mojsilovic, Kush R. Varshney

IBM J. Res. Dev., 2017

Understanding the ecospace of philanthropic projects.

H. Lamba, M. E. Helander, Moninder Singh, N. Lethif, Achyutram Bhamidipaty, S. A. Baset, Aleksandra Mojsilovic, Kush R. Varshney

IBM J. Res. Dev., 2017

Propensity modeling for employee Re-skilling.

Moninder Singh, Karthikeyan Natesan Ramamurthy, Shrihari Vasudevan

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

A configurable, big data system for on-demand healthcare cost prediction.

Karthikeyan Natesan Ramamurthy, Dennis Wei, Emily Ray, Moninder Singh, Vijay S. Iyengar, Dmitriy A. Katz-Rogozhnikov, Jingwei Yang, Kevin N. Tran, Gigi Y. Yuen-Reed

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

Statistical Analysis of Peer Detailing for Children's Diarrhea Treatments.

Yumeng Tao, Debarun Bhattacharjya, Aliza R. Heching, Aditya Vempaty, Moninder Singh, Felix Lam, Kush R. Varshney, Aleksandra Mojsilovic

Proceedings of the 2017 AAAI Spring Symposia, 2017

2015

Identifying Employees for Re-skilling Using an Analytics-Based Approach.

Karthikeyan Natesan Ramamurthy, Moninder Singh, Michael Davis, J. Alex Kevern, Uri Klein, Michael Peran

Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

A talent management tool using propensity to leave analytics.

Karthikeyan Natesan Ramamurthy, Moninder Singh, Yichong Yu, Jessica Aspis, Matthew Iames, Michael Peran, Qin S. Held

Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

2013

Quantile regression for workforce analytics.

Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Moninder Singh

Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

2012

Sales-force performance analytics and optimization.

Moritz Baier, Jorge E. Carballo, Alice J. Chang, Yingdong Lu, Aleksandra Mojsilovic, M. Jonathan Richard, Moninder Singh, Mark S. Squillante, Kush R. Varshney

IBM J. Res. Dev., 2012

Decision trees for heterogeneous dose-response signal analysis.

Kush R. Varshney, Moninder Singh, Jun Wang

Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Does selection bias blind performance diagnostics of business decision models? A case study in salesforce optimization.

Jun Wang, Moninder Singh, Kush R. Varshney

Proceedings of 2012 IEEE International Conference on Service Operations and Logistics, 2012

Interactive Visual Salesforce Analytics.

Kush R. Varshney, Jamie C. Rasmussen, Aleksandra Mojsilovic, Moninder Singh, Joan Morris DiMicco

Proceedings of the International Conference on Information Systems, 2012

An Analytics Approach for Proactively Combating Voluntary Attrition of Employees.

Moninder Singh, Kush R. Varshney, Jun Wang, Aleksandra Mojsilovic, Alisia R. Gill, Patricia I. Faur, Raphael Ezry

Proceedings of the 12th IEEE International Conference on Data Mining Workshops, 2012

2011

Estimating Post-Event Seller Productivity Profiles in Dynamic Sales Organizations.

Kush R. Varshney, Moninder Singh, Mayank Sharma, Aleksandra Mojsilovic

Proceedings of the Data Mining Workshops (ICDMW), 2011

MCMC inference of the shape and variability of time-response signals.

Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Aleksandra Mojsilovic, Moninder Singh

Proceedings of the IEEE International Conference on Acoustics, 2011

2009

Winning the KDD Cup Orange Challenge with Ensemble Selection.

Alexandru Niculescu-Mizil, Claudia Perlich, Grzegorz Swirszcz, Vikas Sindhwani, Yan Liu, Prem Melville, Dong Wang, Jing Xiao, Jianying Hu, Moninder Singh, Wei Xiong Shang, Yanfeng Zhu

Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009, 2009

A framework for combined bayesian analysis and optimization for services delivery.

Afsaneh Shirazi, Jianying Hu, Moninder Singh, Mark S. Squillante, Aleksandra Mojsilovic

Proceedings of the 2009 IEEE/INFORMS International Conference on Service Operations, 2009

2008

K-means clustering of proportional data using L1 distance.

Hisashi Kashima, Jianying Hu, Bonnie K. Ray, Moninder Singh

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Categorization using semi-supervised clustering.

Jianying Hu, Moninder Singh, Aleksandra Mojsilovic

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

2007

Statistical methods for automated generation of service engagement staffing plans.

Jianying Hu, Bonnie K. Ray, Moninder Singh

IBM J. Res. Dev., 2007

2005

Automated cleansing for spend analytics.

Moninder Singh, Jayant Kalagnanam, Sudhir Verma, Amit J. Shah, Swaroop K. Chalasani

Proceedings of the 2005 ACM CIKM International Conference on Information and Knowledge Management, Bremen, Germany, October 31, 2005

2004

Data Protection and Data Sharing in Telematics.

Sastry Duri, Jeffrey Elliott, Marco Gruteser, Xuan Liu, Paul Moskowitz, Ronald Perez, Moninder Singh, Jung-Mu Tang

Mob. Networks Appl., 2004

A system for automated mapping of bill-of-materials part numbers.

Jayant Kalagnanam, Moninder Singh, Sudhir Verma, Michael Patek, Yuk Wah Wong

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

2003

Object Oriented XML Query by Example.

Kathy Bohrer, Xuan Liu, Sean McLaughlin, Edith Schonberg, Moninder Singh

Proceedings of the Conceptual Modeling for Novel Application Domains, 2003

2002

An architecture of diversity for commonsense reasoning.

John McCarthy, Marvin Minsky, Aaron Sloman, Leiguang Gong, Tessa A. Lau, Leora Morgenstern, Erik T. Mueller, Doug Riecken, Moninder Singh, Push Singh

IBM Syst. J., 2002

Framework for security and privacy in automotive telematics.

Sastry Duri, Marco Gruteser, Xuan Liu, Paul Moskowitz, Ronald Perez, Moninder Singh, Jung-Mu Tang

Proceedings of the 2nd International Workshop on Mobile Commerce, 2002

2000

Algebra jam: supporting teamwork and managing roles in a collaborative learning environment.

Mark K. Singley, Moninder Singh, Peter G. Fairweather, Robert G. Farrell, Steven Swerling

Proceedings of the CSCW 2000, 2000

1997

An Expert System Using Nonmonotonic Techniques for Beneefits Inquiry in the Insurance Industry.

Leora Morgenstern, Moninder Singh

Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

Learning Bayesian Networks from Incomplete Data.

Moninder Singh

Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference, 1997

1996

Path Consistency Revisited.

Moninder Singh

Int. J. Artif. Intell. Tools, 1996

Data Mining and Model Simplicity: A Case Study in Diagnosis.

Gregory M. Provan, Moninder Singh

Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

Efficient Learning of Selective Bayesian Network Classifiers.

Moninder Singh, Gregory M. Provan

Proceedings of the Machine Learning, 1996

Learning Goal Oriented Bayesian Networks for Telecommunications Risk Management.

Kazuo J. Ezawa, Moninder Singh, Steven W. Norton

Proceedings of the Machine Learning, 1996

Dynamic Constraint-Based Planning in Trauma Management.

Moninder Singh

Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

Induction of Selective Bayesian Networks from Data.

Moninder Singh

Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1995

Construction of Bayesian network structures from data: A brief survey and an efficient algorithm.

Moninder Singh, Marco Valtorta

Int. J. Approx. Reason., 1995

A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers.

Moninder Singh, Gregory M. Provan

Proceedings of the Machine Learning, 1995

Learning Bayesian Networks Using Feature Selection.

Gregory M. Provan, Moninder Singh

Proceedings of the Learning from Data, 1995

1993

An Algorithm for the Construction of Bayesian Network Structures from Data.

Moninder Singh, Marco Valtorta

Proceedings of the UAI '93: Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence, 1993