An Algorithm for the Construction of Bayesian Network Structures from Data. - Moninder Singh; Marco Valtorta (UAI, 1993)

Learning Bayesian Networks Using Feature Selection. - Gregory M. Provan; Moninder Singh (AISTATS, 1995)

A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers. - Moninder Singh; Gregory M. Provan (ICML, 1995)

Construction of Bayesian network structures from data: A brief survey and an efficient algorithm. - Moninder Singh; Marco Valtorta (Int. J. Approx. Reason., 1995)

Induction of Selective Bayesian Networks from Data. - Moninder Singh (AAAI/IAAI, Vol. 2, 1996)

Dynamic Constraint-Based Planning in Trauma Management. - Moninder Singh (AAAI/IAAI, Vol. 2, 1996)

Learning Goal Oriented Bayesian Networks for Telecommunications Risk Management. - Kazuo J. Ezawa; Moninder Singh; Steven W. Norton (ICML, 1996)

Efficient Learning of Selective Bayesian Network Classifiers. - Moninder Singh; Gregory M. Provan (ICML, 1996)

Data Mining and Model Simplicity: A Case Study in Diagnosis. - Gregory M. Provan; Moninder Singh (KDD, 1996)

Path Consistency Revisited. - Moninder Singh (Int. J. Artif. Intell. Tools, 1996)

Learning Bayesian Networks from Incomplete Data. - Moninder Singh (AAAI/IAAI, 1997)

An Expert System Using Nonmonotonic Techniques for Beneefits Inquiry in the Insurance Industry. - Leora Morgenstern; Moninder Singh (IJCAI (1), 1997)

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 (CSCW, 2000)

Framework for security and privacy in automotive telematics. - Sastry Duri; Marco Gruteser; Xuan Liu; Paul Moskowitz; Ronald Perez; Moninder Singh; Jung-Mu Tang (Workshop Mobile Commerce, 2002)

An architecture of diversity for commonsense reasoning. - John McCarthy 001; Marvin Minsky; Aaron Sloman; Leiguang Gong; Tessa A. Lau; Leora Morgenstern; Erik T. Mueller; Doug Riecken; Moninder Singh; Push Singh (IBM Syst. J., 2002)

Object Oriented XML Query by Example. - Kathy Bohrer; Xuan Liu; Sean McLaughlin; Edith Schonberg; Moninder Singh (ER (Workshops), 2003)

A system for automated mapping of bill-of-materials part numbers. - Jayant Kalagnanam; Moninder Singh; Sudhir Verma; Michael Patek; Yuk Wah Wong (KDD, 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)

Automated cleansing for spend analytics. - Moninder Singh; Jayant Kalagnanam; Sudhir Verma; Amit J. Shah; Swaroop K. Chalasani (CIKM, 2005)

Statistical methods for automated generation of service engagement staffing plans. - Jianying Hu; Bonnie K. Ray; Moninder Singh (IBM J. Res. Dev., 2007)

Categorization using semi-supervised clustering. - Jianying Hu; Moninder Singh; Aleksandra Mojsilovic (ICPR, 2008)

K-means clustering of proportional data using L1 distance. - Hisashi Kashima; Jianying Hu; Bonnie K. Ray; Moninder Singh (ICPR, 2008)

A framework for combined bayesian analysis and optimization for services delivery. - Afsaneh Shirazi; Jianying Hu; Moninder Singh; Mark S. Squillante; Aleksandra Mojsilovic (SOLI, 2009)

Winning the KDD Cup Orange Challenge with Ensemble Selection. - Alexandru Niculescu-Mizil; Claudia Perlich; Grzegorz Swirszcz; Vikas Sindhwani; Yan Liu 002; Prem Melville; Dong Wang; Jing Xiao; Jianying Hu; Moninder Singh; Wei Xiong Shang; Yanfeng Zhu 001 (KDD Cup, 2009)

MCMC inference of the shape and variability of time-response signals. - Dmitriy A. Katz-Rogozhnikov; Kush R. Varshney; Aleksandra Mojsilovic; Moninder Singh (ICASSP, 2011)

Estimating Post-Event Seller Productivity Profiles in Dynamic Sales Organizations. - Kush R. Varshney; Moninder Singh; Mayank Sharma; Aleksandra Mojsilovic (ICDM Workshops, 2011)

An Analytics Approach for Proactively Combating Voluntary Attrition of Employees. - Moninder Singh; Kush R. Varshney; Jun Wang 006; Aleksandra Mojsilovic; Alisia R. Gill; Patricia I. Faur; Raphael Ezry (ICDM Workshops, 2012)

Interactive Visual Salesforce Analytics. - Kush R. Varshney; Jamie C. Rasmussen; Aleksandra Mojsilovic; Moninder Singh; Joan Morris DiMicco (ICIS, 2012)

Does selection bias blind performance diagnostics of business decision models? A case study in salesforce optimization. - Jun Wang 006; Moninder Singh; Kush R. Varshney (SOLI, 2012)

Decision trees for heterogeneous dose-response signal analysis. - Kush R. Varshney; Moninder Singh; Jun Wang 006 (SSP, 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)

Quantile regression for workforce analytics. - Karthikeyan Natesan Ramamurthy; Kush R. Varshney; Moninder Singh (GlobalSIP, 2013)

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 (DSAA, 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 (ICDM Workshops, 2015)

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 (AAAI Spring Symposia, 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 (IEEE BigData, 2017)

Propensity modeling for employee Re-skilling. - Moninder Singh; Karthikeyan Natesan Ramamurthy; Shrihari Vasudevan (GlobalSIP, 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)

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; et al. (IBM J. Res. Dev., 2017)

Assessing National Development Plans for Alignment With Sustainable Development Goals via Semantic Search. - Jonathan Galsurkar; Moninder Singh; Lingfei Wu 001; Aditya Vempaty; Mikhail Sushkov; Devika Iyer; Serge Kapto; Kush R. Varshney (AAAI, 2018)

Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration. - Ritesh Noothigattu; Djallel Bouneffouf 001; Nicholas Mattei; Rachita Chandra; Piyush Madan; Kush R. Varshney; Murray Campbell; Moninder Singh; Francesca Rossi 001 (CoRR, 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; et al. (CoRR, 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)

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; et al. (CoRR, 2019)

Understanding racial bias in health using the Medical Expenditure Panel Survey data. - Moninder Singh; Karthikeyan Natesan Ramamurthy (CoRR, 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; et al. (IBM J. Res. Dev., 2019)

Teaching AI agents ethical values using reinforcement learning and policy orchestration. - Ritesh Noothigattu; Djallel Bouneffouf 001; Nicholas Mattei; Rachita Chandra; Piyush Madan; Kush R. Varshney; Murray Campbell; Moninder Singh; Francesca Rossi 001 (IBM J. Res. Dev., 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; et al. (IEEE Softw., 2019)

Introduction to Explainable AI. - Q. Vera Liao; Moninder Singh; Yunfeng Zhang; Rachel K. E. Bellamy (CHI Extended Abstracts, 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; et al. (FAT*, 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; et al. (J. Mach. Learn. Res., 2020)

Anomaly Attribution with Likelihood Compensation. - Tsuyoshi Idé; Amit Dhurandhar; Jirí Navrátil 001; Moninder Singh; Naoki Abe (AAAI, 2021)

Introduction to AI Fairness. - Yunfeng Zhang; Rachel K. E. Bellamy; Q. Vera Liao; Moninder Singh (CHI Extended Abstracts, 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; et al. (COMAD/CODS, 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)

An Empirical Study of Accuracy, Fairness, Explainability, Distributional Robustness, and Adversarial Robustness. - Moninder Singh; Gevorg Ghalachyan; Kush R. Varshney; Reginald E. Bryant (CoRR, 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)

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; et al. (AAAI, 2022)

Your fairness may vary: Pretrained language model fairness in toxic text classification. - Ioana Baldini; Dennis Wei; Karthikeyan Natesan Ramamurthy; Moninder Singh; Mikhail Yurochkin (ACL (Findings), 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 (AIES, 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 (NeurIPS, 2022)

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)

SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models. - Manish Nagireddy; Lamogha Chiazor; Moninder Singh; Ioana Baldini (AAAI, 2024)

Ranking Large Language Models without Ground Truth. - Amit Dhurandhar; Rahul Nair; Moninder Singh; Elizabeth Daly; Karthikeyan Natesan Ramamurthy (ACL (Findings), 2024)

Reasoning about concepts with LLMs: Inconsistencies abound. - Rosario Uceda-Sosa; Karthikeyan Natesan Ramamurthy; Maria Chang 001; Moninder Singh (CoRR, 2024)

Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations. - Swapnaja Achintalwar; Ioana Baldini; Djallel Bouneffouf 001; Joan Byamugisha; Maria Chang 001; Pierre L. Dognin; Eitan Farchi; Ndivhuwo Makondo; Aleksandra Mojsilovic; Manish Nagireddy; Karthikeyan Natesan Ramamurthy; Inkit Padhi; et al. (IEEE Internet Comput., 2024)