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2020 – today
- 2024
[c48]Manish Nagireddy, Lamogha Chiazor, Moninder Singh, Ioana Baldini:
SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models. AAAI 2024: 21454-21462- [c47]Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy:
Ranking Large Language Models without Ground Truth. ACL (Findings) 2024: 2431-2452 - [i17]Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy:
Ranking Large Language Models without Ground Truth. CoRR abs/2402.14860 (2024) - [i16]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:
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations. CoRR abs/2403.09704 (2024) - [i15]Rosario Uceda-Sosa, Karthikeyan Natesan Ramamurthy, Maria Chang, Moninder Singh:
Reasoning about concepts with LLMs: Inconsistencies abound. CoRR abs/2405.20163 (2024) - 2023
- [i14]Manish Nagireddy, Moninder Singh, Samuel C. Hoffman, Evaline Ju, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions. CoRR abs/2302.09190 (2023) - [i13]Manish Nagireddy, Lamogha Chiazor, Moninder Singh, Ioana Baldini:
SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models. CoRR abs/2312.07492 (2023) - 2022
- [c46]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:
AI Explainability 360: Impact and Design. AAAI 2022: 12651-12657 - [c45]Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh, Mikhail Yurochkin:
Your fairness may vary: Pretrained language model fairness in toxic text classification. ACL (Findings) 2022: 2245-2262 - [c44]Hammaad Adam, Ming-Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi:
Write It Like You See It: Detectable Differences in Clinical Notes by Race Lead to Differential Model Recommendations. AIES 2022: 7-21 - [c43]Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney, Elizabeth Daly, Moninder Singh:
On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach. NeurIPS 2022 - [i12]Hammaad Adam, Ming-Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi:
Write It Like You See It: Detectable Differences in Clinical Notes By Race Lead To Differential Model Recommendations. CoRR abs/2205.03931 (2022) - [i11]Tsuyoshi Idé, Amit Dhurandhar, Jirí Navrátil, Moninder Singh, Naoki Abe:
Anomaly Attribution with Likelihood Compensation. CoRR abs/2208.10679 (2022) - [i10]Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney, Elizabeth M. Daly, Moninder Singh:
On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach. CoRR abs/2211.01498 (2022) - 2021
- [c42]Tsuyoshi Idé, Amit Dhurandhar, Jirí Navrátil, Moninder Singh, Naoki Abe:
Anomaly Attribution with Likelihood Compensation. AAAI 2021: 4131-4138 - [c41]Q. Vera Liao, Moninder Singh, Yunfeng Zhang, Rachel K. E. Bellamy:
Introduction to Explainable AI. CHI Extended Abstracts 2021: 127:1-127:3 - [c40]Yunfeng Zhang, Rachel K. E. Bellamy, Q. Vera Liao, Moninder Singh:
Introduction to AI Fairness. CHI Extended Abstracts 2021: 128:1-128:3 - [c39]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:
AI Explainability 360 Toolkit. COMAD/CODS 2021: 376-379 - [i9]Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Mikhail Yurochkin, Moninder Singh:
Your fairness may vary: Group fairness of pretrained language models in toxic text classification. CoRR abs/2108.01250 (2021) - [i8]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:
AI Explainability 360: Impact and Design. CoRR abs/2109.12151 (2021) - [i7]Moninder Singh, Gevorg Ghalachyan, Kush R. Varshney, Reginald E. Bryant:
An Empirical Study of Accuracy, Fairness, Explainability, Distributional Robustness, and Adversarial Robustness. CoRR abs/2109.14653 (2021) - [i6]Kofi Arhin, Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh:
Ground-Truth, Whose Truth? - Examining the Challenges with Annotating Toxic Text Datasets. CoRR abs/2112.03529 (2021) - 2020
- [j13]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:
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models. J. Mach. Learn. Res. 21: 130:1-130:6 (2020) - [c38]Q. Vera Liao, Moninder Singh, Yunfeng Zhang, Rachel K. E. Bellamy:
Introduction to Explainable AI. CHI Extended Abstracts 2020: 1-4 - [c37]Yunfeng Zhang, Rachel K. E. Bellamy, Moninder Singh, Q. Vera Liao:
Introduction to AI Fairness. CHI Extended Abstracts 2020: 1-4 - [c36]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:
AI explainability 360: hands-on tutorial. FAT* 2020: 696
2010 – 2019
- 2019
- [j12]Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi:
Teaching AI agents ethical values using reinforcement learning and policy orchestration. IBM J. Res. Dev. 63(4/5): 2:1-2:9 (2019) - [j11]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:
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias. IBM J. Res. Dev. 63(4/5): 4:1-4:15 (2019) - [j10]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:
Think Your Artificial Intelligence Software Is Fair? Think Again. IEEE Softw. 36(4): 76-80 (2019) - [c35]Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi:
Teaching AI Agents Ethical Values Using Reinforcement Learning and Policy Orchestration. IJCAI 2019: 6377-6381 - [i5]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:
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques. CoRR abs/1909.03012 (2019) - [i4]Moninder Singh, Karthikeyan Natesan Ramamurthy:
Understanding racial bias in health using the Medical Expenditure Panel Survey data. CoRR abs/1911.01509 (2019) - 2018
- [j9]Shrihari Vasudevan, Moninder Singh, Joydeep Mondal, Michael Peran, Benjamin Zweig, Brian Johnston, Rachel Rosenfeld:
Estimating Fungibility Between Skills by Combining Skill Similarities Obtained from Multiple Data Sources. Data Sci. Eng. 3(3): 248-262 (2018) - [c34]Jonathan Galsurkar, Moninder Singh, Lingfei Wu, Aditya Vempaty, Mikhail Sushkov, Devika Iyer, Serge Kapto, Kush R. Varshney:
Assessing National Development Plans for Alignment With Sustainable Development Goals via Semantic Search. AAAI 2018: 7753-7758 - [i3]Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi:
Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration. CoRR abs/1809.08343 (2018) - [i2]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:
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias. CoRR abs/1810.01943 (2018) - 2017
- [j8]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:
Effectiveness of peer detailing in a diarrhea program in Nigeria. IBM J. Res. Dev. 61(6): 1:1-1:12 (2017) - [j7]H. Lamba, M. E. Helander, Moninder Singh, N. Lethif, Achyutram Bhamidipaty, S. A. Baset, Aleksandra Mojsilovic, Kush R. Varshney:
Understanding the ecospace of philanthropic projects. IBM J. Res. Dev. 61(6): 6:1-6:10 (2017) - [c33]Yumeng Tao, Debarun Bhattacharjya, Aliza R. Heching, Aditya Vempaty, Moninder Singh, Felix Lam, Kush R. Varshney, Aleksandra Mojsilovic:
Statistical Analysis of Peer Detailing for Children's Diarrhea Treatments. AAAI Spring Symposia 2017 - [c32]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:
A configurable, big data system for on-demand healthcare cost prediction. IEEE BigData 2017: 1524-1533 - [c31]Moninder Singh, Karthikeyan Natesan Ramamurthy, Shrihari Vasudevan:
Propensity modeling for employee Re-skilling. GlobalSIP 2017: 893-897 - [c30]Shrihari Vasudevan, Moninder Singh, Joydeep Mondal, Michael Peran, Ben Zweig, Brian Johnston, Rachel Rosenfeld:
Estimating Fungibility Between Skills by Combining Skill-Similarities Obtained from Multiple Data Sources. ICDM Workshops 2017: 229-236 - 2015
- [c29]Karthikeyan Natesan Ramamurthy, Moninder Singh, Yichong Yu, Jessica Aspis, Matthew Iames, Michael Peran, Qin S. Held:
A talent management tool using propensity to leave analytics. DSAA 2015: 1-10 - [c28]Karthikeyan Natesan Ramamurthy, Moninder Singh, Michael Davis, J. Alex Kevern, Uri Klein, Michael Peran:
Identifying Employees for Re-skilling Using an Analytics-Based Approach. ICDM Workshops 2015: 345-354 - 2013
- [c27]Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Moninder Singh:
Quantile regression for workforce analytics. GlobalSIP 2013: 1134 - [i1]Moninder Singh, Marco Valtorta:
An Algorithm for the Construction of Bayesian Network Structures from Data. CoRR abs/1303.1485 (2013) - 2012
- [j6]Moritz Baier, Jorge E. Carballo, Alice J. Chang, Yingdong Lu, Aleksandra Mojsilovic, M. Jonathan Richard, Moninder Singh, Mark S. Squillante, Kush R. Varshney:
Sales-force performance analytics and optimization. IBM J. Res. Dev. 56(6): 8 (2012) - [c26]Moninder Singh, Kush R. Varshney, Jun Wang, Aleksandra Mojsilovic, Alisia R. Gill, Patricia I. Faur, Raphael Ezry:
An Analytics Approach for Proactively Combating Voluntary Attrition of Employees. ICDM Workshops 2012: 317-323 - [c25]Kush R. Varshney, Jamie C. Rasmussen, Aleksandra Mojsilovic, Moninder Singh, Joan Morris DiMicco:
Interactive Visual Salesforce Analytics. ICIS 2012 - [c24]Jun Wang, Moninder Singh, Kush R. Varshney:
Does selection bias blind performance diagnostics of business decision models? A case study in salesforce optimization. SOLI 2012: 416-421 - [c23]Kush R. Varshney, Moninder Singh, Jun Wang:
Decision trees for heterogeneous dose-response signal analysis. SSP 2012: 904-907 - 2011
- [c22]Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Aleksandra Mojsilovic, Moninder Singh:
MCMC inference of the shape and variability of time-response signals. ICASSP 2011: 3956-3959 - [c21]Kush R. Varshney, Moninder Singh, Mayank Sharma, Aleksandra Mojsilovic:
Estimating Post-Event Seller Productivity Profiles in Dynamic Sales Organizations. ICDM Workshops 2011: 1191-1198
2000 – 2009
- 2009
- [c20]Afsaneh Shirazi, Jianying Hu, Moninder Singh, Mark S. Squillante, Aleksandra Mojsilovic:
A framework for combined bayesian analysis and optimization for services delivery. SOLI 2009: 382-387 - [c19]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:
Winning the KDD Cup Orange Challenge with Ensemble Selection. KDD Cup 2009: 23-34 - 2008
- [c18]Jianying Hu, Moninder Singh, Aleksandra Mojsilovic:
Categorization using semi-supervised clustering. ICPR 2008: 1-4 - [c17]Hisashi Kashima, Jianying Hu, Bonnie K. Ray, Moninder Singh:
K-means clustering of proportional data using L1 distance. ICPR 2008: 1-4 - 2007
- [j5]Jianying Hu, Bonnie K. Ray, Moninder Singh:
Statistical methods for automated generation of service engagement staffing plans. IBM J. Res. Dev. 51(3/4): 281-294 (2007) - 2005
- [c16]Moninder Singh, Jayant Kalagnanam, Sudhir Verma, Amit J. Shah, Swaroop K. Chalasani:
Automated cleansing for spend analytics. CIKM 2005: 437-445 - 2004
- [j4]Sastry Duri, Jeffrey Elliott, Marco Gruteser, Xuan Liu, Paul Moskowitz, Ronald Perez, Moninder Singh, Jung-Mu Tang:
Data Protection and Data Sharing in Telematics. Mob. Networks Appl. 9(6): 693-701 (2004) - [c15]Jayant Kalagnanam, Moninder Singh, Sudhir Verma, Michael Patek, Yuk Wah Wong:
A system for automated mapping of bill-of-materials part numbers. KDD 2004: 805-810 - 2003
- [c14]Kathy Bohrer, Xuan Liu, Sean McLaughlin, Edith Schonberg, Moninder Singh:
Object Oriented XML Query by Example. ER (Workshops) 2003: 323-329 - 2002
- [j3]John McCarthy, Marvin Minsky, Aaron Sloman, Leiguang Gong, Tessa A. Lau, Leora Morgenstern, Erik T. Mueller, Doug Riecken, Moninder Singh, Push Singh:
An architecture of diversity for commonsense reasoning. IBM Syst. J. 41(3) (2002) - [c13]Sastry Duri, Marco Gruteser, Xuan Liu, Paul Moskowitz, Ronald Perez, Moninder Singh, Jung-Mu Tang:
Framework for security and privacy in automotive telematics. Workshop Mobile Commerce 2002: 25-32 - 2000
- [c12]Mark K. Singley, Moninder Singh, Peter G. Fairweather, Robert G. Farrell, Steven Swerling:
Algebra jam: supporting teamwork and managing roles in a collaborative learning environment. CSCW 2000: 145-154
1990 – 1999
- 1997
- [c11]Moninder Singh:
Learning Bayesian Networks from Incomplete Data. AAAI/IAAI 1997: 534-539 - [c10]Leora Morgenstern, Moninder Singh:
An Expert System Using Nonmonotonic Techniques for Beneefits Inquiry in the Insurance Industry. IJCAI (1) 1997: 655-661 - 1996
- [j2]Moninder Singh:
Path Consistency Revisited. Int. J. Artif. Intell. Tools 5(1-2): 127-142 (1996) - [c9]Moninder Singh:
Induction of Selective Bayesian Networks from Data. AAAI/IAAI, Vol. 2 1996: 1371 - [c8]Moninder Singh:
Dynamic Constraint-Based Planning in Trauma Management. AAAI/IAAI, Vol. 2 1996: 1408 - [c7]Kazuo J. Ezawa, Moninder Singh, Steven W. Norton:
Learning Goal Oriented Bayesian Networks for Telecommunications Risk Management. ICML 1996: 139-147 - [c6]Moninder Singh, Gregory M. Provan:
Efficient Learning of Selective Bayesian Network Classifiers. ICML 1996: 453-461 - [c5]Gregory M. Provan, Moninder Singh:
Data Mining and Model Simplicity: A Case Study in Diagnosis. KDD 1996: 57-62 - 1995
- [j1]Moninder Singh, Marco Valtorta:
Construction of Bayesian network structures from data: A brief survey and an efficient algorithm. Int. J. Approx. Reason. 12(2): 111-131 (1995) - [c4]Gregory M. Provan, Moninder Singh:
Learning Bayesian Networks Using Feature Selection. AISTATS 1995: 291-300 - [c3]Moninder Singh, Gregory M. Provan:
A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers. ICML 1995: 497-505 - [c2]Moninder Singh:
Path consistency revisited. ICTAI 1995: 318-325 - 1993
- [c1]Moninder Singh, Marco Valtorta:
An Algorithm for the Construction of Bayesian Network Structures from Data. UAI 1993: 259-265
Coauthor Index
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last updated on 2024-10-07 21:19 CEST by the dblp team
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