Kush R. Varshney

According to our database, Kush R. Varshney authored at least 199 papers between 2007 and 2024.

Collaborative distances:

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

2024

Contextual Moral Value Alignment Through Context-Based Aggregation.

Pierre L. Dognin, Jesus Rios, Ronny Luss, Inkit Padhi, Matthew D. Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf

CoRR, 2024

A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible food.

Conor M. Artman, Aditya Mate, Ezinne Nwankwo, Aliza Heching, Tsuyoshi Idé, Jirí Navrátil, Karthikeyan Shanmugam, Wei Sun, Kush R. Varshney, Lauri Goldkind, Gidi Kroch, Jaclyn Sawyer, Ian Watson

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

Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations.

Swapnaja Achintalwar, Adriana Alvarado Garcia, Ateret Anaby-Tavor, Ioana Baldini, Sara E. Berger, Bishwaranjan Bhattacharjee, Djallel Bouneffouf, Subhajit Chaudhury, Pin-Yu Chen, Lamogha Chiazor, Elizabeth M. Daly, Rogério Abreu de Paula, Pierre L. Dognin, Eitan Farchi, Soumya Ghosh, Michael Hind, Raya Horesh, George Kour, Ja Young Lee, Erik Miehling, Keerthiram Murugesan, Manish Nagireddy, Inkit Padhi, David Piorkowski, Ambrish Rawat, Orna Raz, Prasanna Sattigeri, Hendrik Strobelt, Sarathkrishna Swaminathan, Christoph Tillmann, Aashka Trivedi, Kush R. Varshney, Dennis Wei, Shalisha Witherspoon, Marcel Zalmanovici

CoRR, 2024

Rethinking Machine Unlearning for Large Language Models.

Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu

CoRR, 2024

Empathy and the Right to Be an Exception: What LLMs Can and Cannot Do.

William Kidder, Jason D'Cruz, Kush R. Varshney

CoRR, 2024

2023

Humble AI.

Bran Knowles, Jason D'Cruz, John T. Richards, Kush R. Varshney

Commun. ACM, September, 2023

The incentive gap in data work in the era of large models.

Katy Ilonka Gero, Payel Das, Pierre L. Dognin, Inkit Padhi, Prasanna Sattigeri, Kush R. Varshney

Nat. Mac. Intell., June, 2023

Skin Tone Analysis for Representation in Educational Materials (STAR-ED) using machine learning.

Girmaw Abebe Tadesse, Celia Cintas, Kush R. Varshney, Peter W. J. Staar, Chinyere Agunwa, Skyler Speakman, Justin Jia, Elizabeth E. Bailey, Ademide Adelekun, Jules Lipoff, Ginikanwa Onyekaba, Jenna C. Lester, Veronica Rotemberg, James Zou, Roxana Daneshjou

npj Digit. Medicine, 2023

Decolonial AI Alignment: Viśesadharma, Argument, and Artistic Expression.

Kush R. Varshney

CoRR, 2023

Keeping Up with the Language Models: Robustness-Bias Interplay in NLI Data and Models.

Ioana Baldini, Chhavi Yadav, Payel Das, Kush R. Varshney

CoRR, 2023

Towards Healthy AI: Large Language Models Need Therapists Too.

Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi, Kush R. Varshney

CoRR, 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

A Banal Account of a Safety-Creativity Tradeoff in Generative AI 163-165.

Kush R. Varshney, Lav R. Varshney

Proceedings of the Joint Proceedings of the IUI 2023 Workshops: HAI-GEN, 2023

What Is Missing in IRM Training and Evaluation? Challenges and Solutions.

Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness.

Brianna Richardson, Prasanna Sattigeri, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Amit Dhurandhar, Juan E. Gilbert

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Trustworthy AI and the Logics of Intersectional Resistance.

Bran Knowles, Jasmine Fledderjohann, John T. Richards, Kush R. Varshney

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Minimax AUC Fairness: Efficient Algorithm with Provable Convergence.

Zhenhuan Yang, Yan Lok Ko, Kush R. Varshney, Yiming Ying

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models.

Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Human-centered explainability for life sciences, healthcare, and medical informatics.

Sanjoy Dey, Prithwish Chakraborty, Bum Chul Kwon, Amit Dhurandhar, Mohamed F. Ghalwash, Fernando J. Suarez Saiz, Kenney Ng, Daby Sow, Kush R. Varshney, Pablo Meyer

Patterns, 2022

Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making.

Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, Richard Tomsett

Proc. ACM Hum. Comput. Interact., 2022

Humble Machines: Attending to the Underappreciated Costs of Misplaced Distrust.

Bran Knowles, Jason D'Cruz, John T. Richards, Kush R. Varshney

CoRR, 2022

Differentially private SGDA for minimax problems.

Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Causal Feature Selection for Algorithmic Fairness.

Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 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

Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting.

Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre L. Dognin, Kush R. Varshney

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

Out-of-Distribution Detection in Dermatology Using Input Perturbation and Subset Scanning.

Hannah Kim, Girmaw Abebe Tadesse, Celia Cintas, Skyler Speakman, Kush R. Varshney

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Uncertainty Quantification 360: A Hands-on Tutorial.

Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang

Proceedings of the CODS-COMAD 2022: 5th Joint International Conference on Data Science & Management of Data (9th ACM IKDD CODS and 27th COMAD), Bangalore, India, January 8, 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

Socially Responsible AI Algorithms: Issues, Purposes, and Challenges.

Lu Cheng, Kush R. Varshney, Huan Liu

J. Artif. Intell. Res., 2021

Interventional Fairness with Indirect Knowledge of Unobserved Protected Attributes.

Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney

Entropy, 2021

A Human-Centered Methodology for Creating AI FactSheets.

John T. Richards, David Piorkowski, Michael Hind, Stephanie Houde, Aleksandra Mojsilovic, Kush R. Varshney

IEEE Data Eng. Bull., 2021

Human-Centered Explainable AI (XAI): From Algorithms to User Experiences.

Q. Vera Liao, Kush R. Varshney

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

Towards Interpreting Zoonotic Potential of Betacoronavirus Sequences With Attention.

Kahini Wadhawan, Payel Das, Barbara A. Han, Ilya R. Fischhoff, Adrian C. Castellanos, Arvind Varsani, Kush R. Varshney

CoRR, 2021

Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI.

Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang

CoRR, 2021

Automated Meta-Analysis: A Causal Learning Perspective.

Lu Cheng, Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Ioana Baldini

CoRR, 2021

Insiders and Outsiders in Research on Machine Learning and Society.

Yu Tao, Kush R. Varshney

CoRR, 2021

Disparate Impact Diminishes Consumer Trust Even for Advantaged Users.

Tim Draws, Zoltán Szlávik, Benjamin Timmermans, Nava Tintarev, Kush R. Varshney, Michael Hind

Proceedings of the Persuasive Technology - 16th International Conference, 2021

CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions.

Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Empirical or Invariant Risk Minimization? A Sample Complexity Perspective.

Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney

Proceedings of the 9th International Conference on Learning Representations, 2021

Treatment Effect Estimation Using Invariant Risk Minimization.

Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar

Proceedings of the IEEE International Conference on Acoustics, 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

Racial Representation Analysis in Dermatology Academic Materials.

Girmaw Abebe Tadesse, Celia Cintas, Roxana Daneshjou, Kush R. Varshney, Peter W. J. Staar, Skyler Speakman, Kenya Andrews, Chinyere Agunwa, Justin Jia, Elizabeth E. Bailey, Jules Lipoff, Ginikanwa Onyekaba, Veronica Rotemberg, Ademide Adelekun, James Y. Zou

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

Beyond Reasonable Doubt: Improving Fairness in Budget-Constrained Decision Making using Confidence Thresholds.

Michiel A. Bakker, Duy Patrick Tu, Krishna P. Gummadi, Alex 'Sandy' Pentland, Kush R. Varshney, Adrian Weller

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Biomedical Interpretable Entity Representations.

Diego García-Olano, Yasumasa Onoe, Ioana Baldini, Joydeep Ghosh, Byron C. Wallace, Kush R. Varshney

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

The Empathy Gap: Why AI Can Forecast Behavior But Cannot Assess Trustworthiness.

Jason D'Cruz, William Kidder, Kush R. Varshney

Proceedings of the Thinking Fast and Slow and Other Cognitive Theories in AI, 2021

Exploring the Efficacy of Generic Drugs in Treating Cancer.

Ioana Baldini, Mariana Bernagozzi, Sulbha Aggarwal, Mihaela A. Bornea, Saksham Chawla, Joppe Geluykens, Dmitriy A. Katz-Rogozhnikov, Pratik Mukherjee, Smruthi Ramesh, Sara Rosenthal, Jagrati Sharma, Kush R. Varshney, Laura B. Kleiman, Pradeep Mangalath, Catherine Del Vecchio Fitz

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

Learning to Initialize Gradient Descent Using Gradient Descent.

Kartik Ahuja, Amit Dhurandhar, Kush R. Varshney

CoRR, 2020

Trust and Transparency in Contact Tracing Applications.

Stacy Hobson, Michael Hind, Aleksandra Mojsilovic, Kush R. Varshney

CoRR, 2020

Fair Data Integration.

Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney

CoRR, 2020

Fairness of Classifiers Across Skin Tones in Dermatology.

Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Tutorial on Human-Centered Explainability for Healthcare.

Prithwish Chakraborty, Bum Chul Kwon, Sanjoy Dey, Amit Dhurandhar, Daniel M. Gruen, Kenney Ng, Daby Sow, Kush R. Varshney

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Inspection of Blackbox Models for Evaluating Vulnerability in Maternal, Newborn, and Child Health.

William Ogallo, Skyler Speakman, Victor Akinwande, Kush R. Varshney, Aisha Walcott-Bryant, Charity Wayua, Komminist Weldemariam

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing.

Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney

Proceedings of the 37th International Conference on Machine Learning, 2020

Invariant Risk Minimization Games.

Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar

Proceedings of the 37th International Conference on Machine Learning, 2020

Preservation of Anomalous Subgroups On Variational Autoencoder Transformed Data.

Samuel C. Maina, Reginald E. Bryant, William O. Ogallo, Kush R. Varshney, Skyler Speakman, Celia Cintas, Aisha Walcott-Bryant, Robert-Florian Samoilescu, Komminist Weldemariam

Proceedings of the 2020 IEEE International Conference on Acoustics, 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

On Mismatched Detection and Safe, Trustworthy Machine Learning.

Kush R. Varshney

Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020

Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines.

Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Experiences with Improving the Transparency of AI Models and Services.

Michael Hind, Stephanie Houde, Jacquelyn Martino, Aleksandra Mojsilovic, David Piorkowski, John T. Richards, Kush R. Varshney

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

Identifying Factors Associated with Neonatal Mortality in Sub-Saharan Africa using Machine Learning.

William Ogallo, Skyler Speakman, Victor Akinwande, Kush R. Varshney, Aisha Walcott, Charity Wayua, Komminist Weldemariam, Claire-Helene Mershon, Nosa Orobaton

Proceedings of the AMIA 2020, 2020

Characterization of Overlap in Observational Studies.

Michael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel A. Brat, David A. Sontag, Kush R. Varshney

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Joint Optimization of AI Fairness and Utility: A Human-Centered Approach.

Yunfeng Zhang, Rachel K. E. Bellamy, Kush R. Varshney

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

Data Augmentation for Discrimination Prevention and Bias Disambiguation.

Shubham Sharma, Yunfeng Zhang, Jesús M. Ríos Aliaga, Djallel Bouneffouf, Vinod Muthusamy, Kush R. Varshney

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications.

Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Event-Driven Continuous Time Bayesian Networks.

Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Fair Enough: Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds.

Michiel A. Bakker, Humberto Riverón Valdés, Duy Patrick Tu, Krishna P. Gummadi, Kush R. Varshney, Adrian Weller, Alex Pentland

Proceedings of the Workshop on Artificial Intelligence Safety, 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

How Data ScientistsWork Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?

Yaoli Mao, Dakuo Wang, Michael J. Muller, Kush R. Varshney, Ioana Baldini, Casey Dugan, Aleksandra Mojsilovic

Proc. ACM Hum. Comput. Interact., 2019

A big data approach to computational creativity: The curious case of Chef Watson.

Lav R. Varshney, Florian Pinel, Kush R. Varshney, Debarun Bhattacharjya, Angela Schörgendorfer, Yi-Min Chee

IBM J. Res. Dev., 2019

Fairness GAN: Generating datasets with fairness properties using a generative adversarial network.

Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney

IBM J. Res. Dev., 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

FactSheets: Increasing trust in AI services through supplier's declarations of conformity.

Matthew Arnold, Rachel K. E. Bellamy, Michael Hind, Stephanie Houde, Sameep Mehta, Aleksandra Mojsilovic, Ravi Nair, Karthikeyan Natesan Ramamurthy, Alexandra Olteanu, David Piorkowski, Darrell Reimer, John T. Richards, Jason Tsay, Kush R. Varshney

IBM J. Res. Dev., 2019

Trustworthy machine learning and artificial intelligence.

Kush R. Varshney

XRDS, 2019

Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies.

Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman

CoRR, 2019

Preservation of Anomalous Subgroups On Machine Learning Transformed Data.

Samuel C. Maina, Reginald E. Bryant, William O. Goal, Robert-Florian Samoilescu, Kush R. Varshney, Komminist Weldemariam

CoRR, 2019

DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning.

Michiel A. Bakker, Duy Patrick Tu, Humberto Riverón Valdés, Krishna P. Gummadi, Kush R. Varshney, Adrian Weller, Alex Pentland

CoRR, 2019

Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets.

Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney

CoRR, 2019

An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy.

Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney

CoRR, 2019

How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?

Yaoli Mao, Dakuo Wang, Michael J. Muller, Kush R. Varshney, Ioana Baldini, Casey Dugan, Aleksandra Mojsilovic

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

Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning.

Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic

CoRR, 2019

Open Platforms for Artificial Intelligence for Social Good: Common Patterns as a Pathway to True Impact.

Kush R. Varshney, Aleksandra Mojsilovic

CoRR, 2019

Topological Data Analysis of Decision Boundaries with Application to Model Selection.

Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Krishnan Mody

Proceedings of the 36th International Conference on Machine Learning, 2019

A Scalable Blockchain Approach for Trusted Computation and Verifiable Simulation in Multi-Party Collaborations.

Ravi Kiran Raman, Roman Vaculín, Michael Hind, Sekou L. Remy, Eleftheria Kyriaki Pissadaki, Nelson Kibichii Bore, Roozbeh Daneshvar, Biplav Srivastava, Kush R. Varshney

Proceedings of the IEEE International Conference on Blockchain and Cryptocurrency, 2019

Promoting Distributed Trust in Machine Learning and Computational Simulation.

Nelson Kibichii Bore, Ravi Kiran Raman, Isaac M. Markus, Sekou L. Remy, Oliver Bent, Michael Hind, Eleftheria Kyriaki Pissadaki, Biplav Srivastava, Roman Vaculín, Kush R. Varshney, Komminist Weldemariam

Proceedings of the IEEE International Conference on Blockchain and Cryptocurrency, 2019

Constructing and Compressing Frames in Blockchain-based Verifiable Multi-party Computation.

Ravi Kiran Raman, Kush R. Varshney, Roman Vaculín, Nelson Kibichii Bore, Sekou L. Remy, Eleftheria Kyriaki Pissadaki, Michael Hind

Proceedings of the IEEE International Conference on Acoustics, 2019

Bias Mitigation Post-processing for Individual and Group Fairness.

Pranay Kr. Lohia, Karthikeyan Natesan Ramamurthy, Manish Bhide, Diptikalyan Saha, Kush R. Varshney, Ruchir Puri

Proceedings of the IEEE International Conference on Acoustics, 2019

TED: Teaching AI to Explain its Decisions.

Michael Hind, Dennis Wei, Murray Campbell, Noel C. F. Codella, Amit Dhurandhar, Aleksandra Mojsilovic, Karthikeyan Natesan Ramamurthy, Kush R. Varshney

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Fair Transfer Learning with Missing Protected Attributes.

Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

Legislative Prediction with Political and Social Network Analysis.

Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic

Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Distribution-preserving k-anonymity.

Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney

Stat. Anal. Data Min., 2018

Data Pre-Processing for Discrimination Prevention: Information-Theoretic Optimization and Analysis.

Flávio du Pin Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney

IEEE J. Sel. Top. Signal Process., 2018

Understanding Unequal Gender Classification Accuracy from Face Images.

Vidya Muthukumar, Tejaswini Pedapati, Nalini K. Ratha, Prasanna Sattigeri, Chai-Wah Wu, Brian Kingsbury, Abhishek Kumar, Samuel Thomas, Aleksandra Mojsilovic, Kush R. Varshney

CoRR, 2018

SimplerVoice: A Key Message & Visual Description Generator System for Illiteracy.

Minh N. B. Nguyen, Samuel Thomas, Anne E. Gattiker, Sujatha Kashyap, Kush R. Varshney

CoRR, 2018

Promoting Distributed Trust in Machine Learning and Computational Simulation via a Blockchain Network.

Nelson Kibichii Bore, Ravi Kiran Raman, Isaac M. Markus, Sekou L. Remy, Oliver Bent, Michael Hind, Eleftheria Kyriaki Pissadaki, Biplav Srivastava, Roman Vaculín, Kush R. Varshney, Komminist Weldemariam

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, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang

CoRR, 2018

Trusted Multi-Party Computation and Verifiable Simulations: A Scalable Blockchain Approach.

Ravi Kiran Raman, Roman Vaculín, Michael Hind, Sekou L. Remy, Eleftheria Kyriaki Pissadaki, Nelson Kibichii Bore, Roozbeh Daneshvar, Biplav Srivastava, Kush R. Varshney

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

Increasing Trust in AI Services through Supplier's Declarations of Conformity.

Michael Hind, Sameep Mehta, Aleksandra Mojsilovic, Ravi Nair, Karthikeyan Natesan Ramamurthy, Alexandra Olteanu, Kush R. Varshney

CoRR, 2018

Teaching machines to understand data science code by semantic enrichment of dataflow graphs.

Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney

CoRR, 2018

Proceedings of the 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018).

Been Kim, Kush R. Varshney, Adrian Weller

CoRR, 2018

Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory.

Kush R. Varshney, Prashant Khanduri, Pranay Sharma, Shan Zhang, Pramod K. Varshney

CoRR, 2018

Teaching Meaningful Explanations.

Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic

CoRR, 2018

Fairness GAN.

Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney

CoRR, 2018

Structure Learning from Time Series with False Discovery Control.

Bernat Guillen Pegueroles, Bhanukiran Vinzamuri, Karthikeyan Shanmugam, Steve Hedden, Jonathan D. Moyer, Kush R. Varshney

CoRR, 2018

How an Electrical Engineer Became an Artificial Intelligence Researcher, a Multiphase Active Contours Analysis.

Kush R. Varshney

CoRR, 2018

Semantic Representation of Data Science Programs.

Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

The Effect of Extremist Violence on Hateful Speech Online.

Alexandra Olteanu, Carlos Castillo, Jeremy Boy, Kush R. Varshney

Proceedings of the Twelfth International Conference on Web and Social Media, 2018

False Discovery Rate Control with Concave Penalties Using Stability Selection.

Bhanukiran Vinzamuri, Kush R. Varshney

Proceedings of the 2018 IEEE Data Science Workshop, 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

Signal Processing for Social Good [In the Spotlight].

Kush R. Varshney

IEEE Signal Process. Mag., 2017

Decision Making With Quantized Priors Leads to Discrimination.

Lav R. Varshney, Kush R. Varshney

Proc. IEEE, 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

Real-time understanding of humanitarian crises via targeted information retrieval.

Kien Pham, Prasanna Sattigeri, Amit Dhurandhar, A. C. Jacob, M. Vukovic, P. Chataigner, Juliana Freire, Aleksandra Mojsilovic, Kush R. Varshney

IBM J. Res. Dev., 2017

Dataflow representation of data analyses: Toward a platform for collaborative data science.

Evan Patterson, Robert N. McBurney, H. Schmidt, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney

IBM J. Res. Dev., 2017

Preface: Data Science for Social Good.

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

How to foster innovation: A data-driven approach to measuring economic competitiveness.

Caitlin Kuhlman, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Aurélie C. Lozano, Lei Cao, C. Reddy, Aleksandra Mojsilovic, Kush R. Varshney

IBM J. Res. Dev., 2017

Neurology-as-a-Service for the Developing World.

Tejas Dharamsi, Payel Das, Tejaswini Pedapati, Gregory Bramble, Vinod Muthusamy, Horst Samulowitz, Kush R. Varshney, Yuvaraj Rajamanickam, John Thomas, Justin Dauwels

CoRR, 2017

An End-To-End Machine Learning Pipeline That Ensures Fairness Policies.

Samiulla Shaikh, Harit Vishwakarma, Sameep Mehta, Kush R. Varshney, Karthikeyan Natesan Ramamurthy, Dennis Wei

CoRR, 2017

Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017).

Been Kim, Dmitry M. Malioutov, Kush R. Varshney, Adrian Weller

CoRR, 2017

Positive-Unlabeled Demand-Aware Recommendation.

Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li

CoRR, 2017

Optimized Data Pre-Processing for Discrimination Prevention.

Flávio du Pin Calmon, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney

CoRR, 2017

On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products.

Kush R. Varshney, Homa Alemzadeh

Big Data, 2017

The Limits of Abstract Evaluation Metrics: The Case of Hate Speech Detection.

Alexandra Olteanu, Kartik Talamadupula, Kush R. Varshney

Proceedings of the 2017 ACM on Web Science Conference, 2017

Scalable Demand-Aware Recommendation.

Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Optimized Pre-Processing for Discrimination Prevention.

Flávio P. Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 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

Machine Representation of Data Analyses: Towards a Platform for Collaborative Data Science.

Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney

Proceedings of the 2017 AAAI Spring Symposia, 2017

2016

Olfactory signal processing.

Kush R. Varshney, Lav R. Varshney

Digit. Signal Process., 2016

Proceedings of the 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications.

Kush R. Varshney

CoRR, 2016

Understanding Innovation to Drive Sustainable Development.

Prasanna Sattigeri, Aurélie C. Lozano, Aleksandra Mojsilovic, Kush R. Varshney, Mahmoud Naghshineh

CoRR, 2016

Proceedings of the 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016).

Been Kim, Dmitry M. Malioutov, Kush R. Varshney

CoRR, 2016

Learning sparse two-level boolean rules.

Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov

Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Dynamic matrix factorization with social influence.

Aleksandr Y. Aravkin, Kush R. Varshney, Liu Yang

Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Engineering safety in machine learning.

Kush R. Varshney

Proceedings of the 2016 Information Theory and Applications Workshop, 2016

Stable estimation of Granger-causal factors of country-level innovation.

Aurélie C. Lozano, Prasanna Sattigeri, Aleksandra Mojsilovic, Kush R. Varshney

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Fidelity loss in distribution-preserving anonymization and histogram equalization.

Lav R. Varshney, Kush R. Varshney

Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

Information retrieval, fusion, completion, and clustering for employee expertise estimation.

Raya Horesh, Kush R. Varshney, Jinfeng Yi

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Interpretable machine learning via convex cardinal shape composition.

Kush R. Varshney

Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015

Data Challenges in Disease Response: The 2014 Ebola Outbreak and Beyond.

Kush R. Varshney, Dennis Wei, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic

ACM J. Data Inf. Qual., 2015

Interpretable Two-level Boolean Rule Learning for Classification.

Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov

CoRR, 2015

Targeting Villages for Rural Development Using Satellite Image Analysis.

Kush R. Varshney, George H. Chen, Brian Abelson, Kendall Nowocin, Vivek Sakhrani, Ling Xu, Brian L. Spatocco

Big Data, 2015

Health Insurance Market Risk Assessment: Covariate Shift and k-Anonymity.

Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Assessing Expertise in the Enterprise: The Recommender Point of View.

Aleksandra Mojsilovic, Kush R. Varshney

Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Robust binary hypothesis testing under contaminated likelihoods.

Dennis Wei, Kush R. Varshney

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Persistent topology of decision boundaries.

Kush R. Varshney, Karthikeyan Natesan Ramamurthy

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Learning interpretable classification rules using sequential rowsampling.

Sanjeeb Dash, Dmitry M. Malioutov, Kush R. Varshney

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Optigrow: People Analytics for Job Transfers.

Dennis Wei, Kush R. Varshney, Marcy Wagman

Proceedings of the 2015 IEEE International Congress on Big Data, New York City, NY, USA, June 27, 2015

2014

Legislative Prediction with Political and Social Network Analysis.

Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic

Encyclopedia of Social Network Analysis and Mining, 2014

Collaborative Kalman Filtering for Dynamic Matrix Factorization.

John Z. Sun, Dhruv Parthasarathy, Kush R. Varshney

IEEE Trans. Signal Process., 2014

Optimal Grouping for Group Minimax Hypothesis Testing.

Kush R. Varshney, Lav R. Varshney

IEEE Trans. Inf. Theory, 2014

Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing.

Müjdat Çetin, Ivana Stojanovic, N. Özben Önhon, Kush R. Varshney, Sadegh Samadi, William Clement Karl, Alan S. Willsky

IEEE Signal Process. Mag., 2014

Bounded Confidence Opinion Dynamics in a Social Network of Bayesian Decision Makers.

Kush R. Varshney

IEEE J. Sel. Top. Signal Process., 2014

Olfactory Signals and Systems.

Kush R. Varshney, Lav R. Varshney

CoRR, 2014

Active odor cancellation.

Kush R. Varshney, Lav R. Varshney

Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

FOOD steganography with olfactory white.

Kush R. Varshney, Lav R. Varshney

Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Computing persistent homology under random projection.

Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Jayaraman J. Thiagarajan

Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Predicting employee expertise for talent management in the enterprise.

Kush R. Varshney, Vijil Chenthamarakshan, Scott W. Fancher, Jun Wang, DongPing Fang, Aleksandra Mojsilovic

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Targeting direct cash transfers to the extremely poor.

Brian Abelson, Kush R. Varshney, Joy Sun

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Screening for learning classification rules via Boolean compressed sensing.

Sanjeeb Dash, Dmitry M. Malioutov, Kush R. Varshney

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Practical Ensemble Classification Error Bounds for Different Operating Points.

Kush R. Varshney, Ryan J. Prenger, Tracy L. Marlatt, Barry Y. Chen, William G. Hanley

IEEE Trans. Knowl. Data Eng., 2013

Flavor Pairing in Medieval European Cuisine: A Study in Cooking with Dirty Data.

Kush R. Varshney, Lav R. Varshney, Jun Wang, Daniel Myers

CoRR, 2013

A Big Data Approach to Computational Creativity.

Lav R. Varshney, Florian Pinel, Kush R. Varshney, Debarun Bhattacharjya, Angela Schörgendorfer, Yi-Min Chee

CoRR, 2013

Balancing lifetime and classification accuracy of wireless sensor networks.

Kush R. Varshney, Peter M. van de Ven

Proceedings of the Fourteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2013

Exact Rule Learning via Boolean Compressed Sensing.

Dmitry M. Malioutov, Kush R. Varshney

Proceedings of the 30th International Conference on Machine Learning, 2013

Prescriptive Analytics for Allocating Sales Teams to Opportunities.

Ban Kawas, Mark S. Squillante, Dharmashankar Subramanian, Kush R. Varshney

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Quantifying and Recommending Expertise When New Skills Emerge.

DongPing Fang, Kush R. Varshney, Jun Wang, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic, John H. Bauer

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Opinion dynamics with bounded confidence in the Bayes risk error divergence sense.

Kush R. Varshney

Proceedings of the IEEE International Conference on Acoustics, 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

Cognition as a part of computational creativity.

Lav R. Varshney, Florian Pinel, Kush R. Varshney, Angela Schörgendorfer, Yi-Min Chee

Proceedings of the IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing, 2013

2012

Generalization Error of Linear Discriminant Analysis in Spatially-Correlated Sensor Networks.

Kush R. Varshney

IEEE Trans. Signal Process., 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

Legislative Prediction via Random Walks over a Heterogeneous Graph.

Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic

Proceedings of the Twelfth SIAM International Conference on Data Mining, 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

Dynamic matrix factorization: A state space approach.

John Z. Sun, Kush R. Varshney, Karthik Subbian

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011

Linear Dimensionality Reduction for Margin-Based Classification: High-Dimensional Data and Sensor Networks.

Kush R. Varshney, Alan S. Willsky

IEEE Trans. Signal Process., 2011

Bayes Risk Error is a Bregman Divergence.

Kush R. Varshney

IEEE Trans. Signal Process., 2011

Business Analytics Based on Financial Time Series.

Kush R. Varshney, Aleksandra Mojsilovic

IEEE Signal Process. Mag., 2011

Categorical decision making by people, committees, and crowds.

Lav R. Varshney, Joong Bum Rhim, Kush R. Varshney, Vivek K. Goyal

Proceedings of the Information Theory and Applications Workshop, 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

Spatially-correlated sensor discriminant analysis.

Kush R. Varshney

Proceedings of the IEEE International Conference on Acoustics, 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

2010

Frugal hypothesis testing and classification.

Kush R. Varshney

PhD thesis, 2010

Classification Using Geometric Level Sets.

Kush R. Varshney, Alan S. Willsky

J. Mach. Learn. Res., 2010

Class-specific error bounds for ensemble classifiers.

Ryan J. Prenger, Tracy D. Lemmond, Kush R. Varshney, Barry Y. Chen, William G. Hanley

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009

Postarthroplasty Examination Using X-Ray Images.

Kush R. Varshney, Nikos Paragios, Jean-François Deux, Alain Kulski, Rémy Raymond, Phillipe Hernigou, Alain Rahmouni

IEEE Trans. Medical Imaging, 2009

Learning dimensionality-reduced classifiers for information fusion.

Kush R. Varshney, Alan S. Willsky

Proceedings of the 12th International Conference on Information Fusion, 2009

2008

Quantization of Prior Probabilities for Hypothesis Testing.

Kush R. Varshney, Lav R. Varshney

IEEE Trans. Signal Process., 2008

Sparse Representation in Structured Dictionaries With Application to Synthetic Aperture Radar.

Kush R. Varshney, Müjdat Çetin, John W. Fisher III, Alan S. Willsky

IEEE Trans. Signal Process., 2008

Minimum mean bayes risk error quantization of prior probabilities.

Kush R. Varshney, Lav R. Varshney

Proceedings of the IEEE International Conference on Acoustics, 2008

2007

Multi-View Stereo Reconstruction of Total Knee Replacement from X-Rays.

Kush R. Varshney, Nikos Paragios, Alain Kulski, Rémy Raymond, Phillipe Hernigou, Alain Rahmouni

Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007