Kush R. Varshney

According to our database1, Kush R. Varshney authored at least 149 papers between 2007 and 2020.

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2020
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making.
CoRR, 2020

Trust and Transparency in Contact Tracing Applications.
CoRR, 2020

Fair Data Integration.
CoRR, 2020

Invariant Risk Minimization Games.
CoRR, 2020

Fairness of Classifiers Across Skin Tones in Dermatology.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Tutorial on Human-Centered Explainability for Healthcare.
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.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Preservation of Anomalous Subgroups On Variational Autoencoder Transformed Data.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020


On Mismatched Detection and Safe, Trustworthy Machine Learning.
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.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Experiences with Improving the Transparency of AI Models and Services.
Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020

Characterization of Overlap in Observational Studies.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Joint Optimization of AI Fairness and Utility: A Human-Centered Approach.
Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

Data Augmentation for Discrimination Prevention and Bias Disambiguation.
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.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Event-Driven Continuous Time Bayesian Networks.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Fair Enough: Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds.
Proceedings of the Workshop on Artificial Intelligence Safety, 2020

2019
Think Your Artificial Intelligence Software Is Fair? Think Again.
IEEE Softw., 2019

How Data ScientistsWork Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?
Proc. ACM Hum. Comput. Interact., 2019

A big data approach to computational creativity: The curious case of Chef Watson.
IBM J. Res. Dev., 2019

Fairness GAN: Generating datasets with fairness properties using a generative adversarial network.
IBM J. Res. Dev., 2019

Teaching AI agents ethical values using reinforcement learning and policy orchestration.
IBM J. Res. Dev., 2019

AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias.
IBM J. Res. Dev., 2019

FactSheets: Increasing trust in AI services through supplier's declarations of conformity.
IBM J. Res. Dev., 2019

Trustworthy machine learning and artificial intelligence.
XRDS, 2019

Experiences with Improving the Transparency of AI Models and Services.
CoRR, 2019

Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies.
CoRR, 2019

Preservation of Anomalous Subgroups On Machine Learning Transformed Data.
CoRR, 2019

DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning.
CoRR, 2019

Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets.
CoRR, 2019

An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy.
CoRR, 2019

How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?
CoRR, 2019

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.
CoRR, 2019

Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning.
CoRR, 2019

Open Platforms for Artificial Intelligence for Social Good: Common Patterns as a Pathway to True Impact.
CoRR, 2019

Teaching AI Agents Ethical Values Using Reinforcement Learning and Policy Orchestration.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Topological Data Analysis of Decision Boundaries with Application to Model Selection.
Proceedings of the 36th International Conference on Machine Learning, 2019

A Scalable Blockchain Approach for Trusted Computation and Verifiable Simulation in Multi-Party Collaborations.
Proceedings of the IEEE International Conference on Blockchain and Cryptocurrency, 2019

Promoting Distributed Trust in Machine Learning and Computational Simulation.
Proceedings of the IEEE International Conference on Blockchain and Cryptocurrency, 2019

Constructing and Compressing Frames in Blockchain-based Verifiable Multi-party Computation.
Proceedings of the IEEE International Conference on Acoustics, 2019

Bias Mitigation Post-processing for Individual and Group Fairness.
Proceedings of the IEEE International Conference on Acoustics, 2019

TED: Teaching AI to Explain its Decisions.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Fair Transfer Learning with Missing Protected Attributes.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018
Legislative Prediction with Political and Social Network Analysis.
Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Distribution-preserving k-anonymity.
Stat. Anal. Data Min., 2018

Data Pre-Processing for Discrimination Prevention: Information-Theoretic Optimization and Analysis.
IEEE J. Sel. Top. Signal Process., 2018

Understanding Unequal Gender Classification Accuracy from Face Images.
CoRR, 2018

SimplerVoice: A Key Message & Visual Description Generator System for Illiteracy.
CoRR, 2018

Promoting Distributed Trust in Machine Learning and Computational Simulation via a Blockchain Network.
CoRR, 2018

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias.
CoRR, 2018

Trusted Multi-Party Computation and Verifiable Simulations: A Scalable Blockchain Approach.
CoRR, 2018

Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration.
CoRR, 2018

Increasing Trust in AI Services through Supplier's Declarations of Conformity.
CoRR, 2018

Teaching machines to understand data science code by semantic enrichment of dataflow graphs.
CoRR, 2018

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

Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory.
CoRR, 2018

Teaching Meaningful Explanations.
CoRR, 2018

Fairness GAN.
CoRR, 2018

Structure Learning from Time Series with False Discovery Control.
CoRR, 2018

How an Electrical Engineer Became an Artificial Intelligence Researcher, a Multiphase Active Contours Analysis.
CoRR, 2018

Semantic Representation of Data Science Programs.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

The Effect of Extremist Violence on Hateful Speech Online.
Proceedings of the Twelfth International Conference on Web and Social Media, 2018

False Discovery Rate Control with Concave Penalties Using Stability Selection.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

Assessing National Development Plans for Alignment With Sustainable Development Goals via Semantic Search.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Signal Processing for Social Good [In the Spotlight].
IEEE Signal Process. Mag., 2017

Decision Making With Quantized Priors Leads to Discrimination.
Proc. IEEE, 2017

Effectiveness of peer detailing in a diarrhea program in Nigeria.
IBM J. Res. Dev., 2017

Real-time understanding of humanitarian crises via targeted information retrieval.
IBM J. Res. Dev., 2017

Dataflow representation of data analyses: Toward a platform for collaborative data science.
IBM J. Res. Dev., 2017

Preface: Data Science for Social Good.
IBM J. Res. Dev., 2017

Understanding the ecospace of philanthropic projects.
IBM J. Res. Dev., 2017

How to foster innovation: A data-driven approach to measuring economic competitiveness.
IBM J. Res. Dev., 2017

Neurology-as-a-Service for the Developing World.
CoRR, 2017

An End-To-End Machine Learning Pipeline That Ensures Fairness Policies.
CoRR, 2017

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

Positive-Unlabeled Demand-Aware Recommendation.
CoRR, 2017

Optimized Data Pre-Processing for Discrimination Prevention.
CoRR, 2017

On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products.
Big Data, 2017

The Limits of Abstract Evaluation Metrics: The Case of Hate Speech Detection.
Proceedings of the 2017 ACM on Web Science Conference, 2017

Scalable Demand-Aware Recommendation.
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.
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.
Proceedings of the 2017 AAAI Spring Symposia, 2017

Machine Representation of Data Analyses: Towards a Platform for Collaborative Data Science.
Proceedings of the 2017 AAAI Spring Symposia, 2017

2016
Olfactory signal processing.
Digit. Signal Process., 2016

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

Understanding Innovation to Drive Sustainable Development.
CoRR, 2016

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

Learning sparse two-level boolean rules.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Dynamic matrix factorization with social influence.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Engineering safety in machine learning.
Proceedings of the 2016 Information Theory and Applications Workshop, 2016

Stable estimation of Granger-causal factors of country-level innovation.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Fidelity loss in distribution-preserving anonymization and histogram equalization.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

Information retrieval, fusion, completion, and clustering for employee expertise estimation.
Proceedings of the 2016 IEEE International Conference on Big Data, 2016

Interpretable machine learning via convex cardinal shape composition.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015
Data Challenges in Disease Response: The 2014 Ebola Outbreak and Beyond.
ACM J. Data Inf. Qual., 2015

Interpretable Two-level Boolean Rule Learning for Classification.
CoRR, 2015

Targeting Villages for Rural Development Using Satellite Image Analysis.
Big Data, 2015

Health Insurance Market Risk Assessment: Covariate Shift and k-Anonymity.
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.
Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Robust binary hypothesis testing under contaminated likelihoods.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Persistent topology of decision boundaries.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Learning interpretable classification rules using sequential rowsampling.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Optigrow: People Analytics for Job Transfers.
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.
Encyclopedia of Social Network Analysis and Mining, 2014

Collaborative Kalman Filtering for Dynamic Matrix Factorization.
IEEE Trans. Signal Process., 2014

Optimal Grouping for Group Minimax Hypothesis Testing.
IEEE Trans. Inf. Theory, 2014

Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing.
IEEE Signal Process. Mag., 2014

Bounded Confidence Opinion Dynamics in a Social Network of Bayesian Decision Makers.
IEEE J. Sel. Top. Signal Process., 2014

Olfactory Signals and Systems.
CoRR, 2014

Active odor cancellation.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

FOOD steganography with olfactory white.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Computing persistent homology under random projection.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Predicting employee expertise for talent management in the enterprise.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Targeting direct cash transfers to the extremely poor.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Screening for learning classification rules via Boolean compressed sensing.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Practical Ensemble Classification Error Bounds for Different Operating Points.
IEEE Trans. Knowl. Data Eng., 2013

Flavor Pairing in Medieval European Cuisine: A Study in Cooking with Dirty Data.
CoRR, 2013

A Big Data Approach to Computational Creativity.
CoRR, 2013

Balancing lifetime and classification accuracy of wireless sensor networks.
Proceedings of the Fourteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2013

Exact Rule Learning via Boolean Compressed Sensing.
Proceedings of the 30th International Conference on Machine Learning, 2013

Prescriptive Analytics for Allocating Sales Teams to Opportunities.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Quantifying and Recommending Expertise When New Skills Emerge.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Opinion dynamics with bounded confidence in the Bayes risk error divergence sense.
Proceedings of the IEEE International Conference on Acoustics, 2013

Quantile regression for workforce analytics.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Cognition as a part of computational creativity.
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.
IEEE Trans. Signal Process., 2012

Sales-force performance analytics and optimization.
IBM J. Res. Dev., 2012

Decision trees for heterogeneous dose-response signal analysis.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Legislative Prediction via Random Walks over a Heterogeneous Graph.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Interactive Visual Salesforce Analytics.
Proceedings of the International Conference on Information Systems, 2012

An Analytics Approach for Proactively Combating Voluntary Attrition of Employees.
Proceedings of the 12th IEEE International Conference on Data Mining Workshops, 2012

Dynamic matrix factorization: A state space approach.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011
Linear Dimensionality Reduction for Margin-Based Classification: High-Dimensional Data and Sensor Networks.
IEEE Trans. Signal Process., 2011

Bayes Risk Error is a Bregman Divergence.
IEEE Trans. Signal Process., 2011

Business Analytics Based on Financial Time Series.
IEEE Signal Process. Mag., 2011

Categorical decision making by people, committees, and crowds.
Proceedings of the Information Theory and Applications Workshop, 2011

Estimating Post-Event Seller Productivity Profiles in Dynamic Sales Organizations.
Proceedings of the Data Mining Workshops (ICDMW), 2011

Spatially-correlated sensor discriminant analysis.
Proceedings of the IEEE International Conference on Acoustics, 2011

MCMC inference of the shape and variability of time-response signals.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
Frugal hypothesis testing and classification.
PhD thesis, 2010

Classification Using Geometric Level Sets.
J. Mach. Learn. Res., 2010

Class-specific error bounds for ensemble classifiers.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009
Postarthroplasty Examination Using X-Ray Images.
IEEE Trans. Medical Imaging, 2009

Learning dimensionality-reduced classifiers for information fusion.
Proceedings of the 12th International Conference on Information Fusion, 2009

2008
Quantization of Prior Probabilities for Hypothesis Testing.
IEEE Trans. Signal Process., 2008

Sparse Representation in Structured Dictionaries With Application to Synthetic Aperture Radar.
IEEE Trans. Signal Process., 2008

Minimum mean bayes risk error quantization of prior probabilities.
Proceedings of the IEEE International Conference on Acoustics, 2008

2007
Multi-View Stereo Reconstruction of Total Knee Replacement from X-Rays.
Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007


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