Dennis Wei

CoRR, 2024

Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs.

[BibT_eX]

[DOI]

Swanand Ravindra Kadhe

CoRR, 2024

Interventional Causal Discovery in a Mixture of DAGs.

[BibT_eX]

[DOI]

Burak Varici

Ali Tajer

CoRR, 2024

Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions.

[BibT_eX]

[DOI]

CoRR, 2024

Selective Explanations.

[BibT_eX]

[DOI]

Lucas Monteiro Paes

CoRR, 2024

The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers.

[BibT_eX]

[DOI]

CoRR, 2024

Multi-Level Explanations for Generative Language Models.

[BibT_eX]

[DOI]

Werner Geyer

Soumya Ghosh

CoRR, 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

Using Causal Inference to Investigate Contraceptive Discontinuation in Sub-Saharan Africa.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Trust Regions for Explanations via Black-Box Probabilistic Certification.

[BibT_eX]

[DOI]

Swagatam Haldar

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Causal Bandits with General Causal Models and Interventions.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Interpretable and Fair Boolean Rule Sets via Column Generation.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Interpretable differencing of machine learning models.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Effective Human-AI Teams via Learned Natural Language Rules and Onboarding.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Statistical Interpretation of the Maximum Subarray Problem.

[BibT_eX]

[DOI]

Dmitry M. Malioutov

Proceedings of the IEEE International Conference on Acoustics, 2023

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

[BibT_eX]

[DOI]

Brianna Richardson

Juan E. Gilbert

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

Adversarial Auditing of Machine Learning Models under Compound Shift.

[BibT_eX]

[DOI]

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Convex Bounds on the Softmax Function with Applications to Robustness Verification.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Who Should Predict? Exact Algorithms For Learning to Defer to Humans.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Heavy Sets with Applications to Interpretable Machine Learning Diagnostics.

[BibT_eX]

[DOI]

Dmitry M. Malioutov

Sanjeeb Dash

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Stress-Testing Bias Mitigation Algorithms to Understand Fairness Vulnerabilities.

[BibT_eX]

[DOI]

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

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

[BibT_eX]

[DOI]

Proc. ACM Hum. Comput. Interact., 2022

Downstream Fairness Caveats with Synthetic Healthcare Data.

[BibT_eX]

[DOI]

CoRR, 2022

Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners.

[BibT_eX]

[DOI]

Zaid Bin Tariq

CoRR, 2022

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

[BibT_eX]

[DOI]

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

FROTE: Feedback Rule-Driven Oversampling for Editing Models.

[BibT_eX]

[DOI]

Oznur Alkan

Massimiliano Mattetti

Rahul Nair

Elizabeth Daly

Diptikalyan Saha

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

Evaluating Fairness of Synthetic Healthcare Data Models.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2022, 2022

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

[BibT_eX]

[DOI]

Ioana Baldini

Moninder Singh

Mikhail Yurochkin

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

AI Explainability 360: Impact and Design.

[BibT_eX]

[DOI]

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

2021

Optimized Score Transformation for Consistent Fair Classification.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

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

[BibT_eX]

[DOI]

Kofi Arhin

Ioana Baldini

Moninder Singh

CoRR, 2021

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

[BibT_eX]

[DOI]

Ioana Baldini

Mikhail Yurochkin

Moninder Singh

CoRR, 2021

Conditionally independent data generation.

[BibT_eX]

[DOI]

Kartik Ahuja

Karthikeyan Shanmugam

Murat Kocaoglu

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions.

[BibT_eX]

[DOI]

Isha Puri

Tejaswini Pedapati

Karthikeyan Shanmugam

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

AIMEE: Interactive model maintenance with rule-based surrogates.

[BibT_eX]

[DOI]

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

What Changed? Interpretable Model Comparison.

[BibT_eX]

[DOI]

Rahul Nair

Massimiliano Mattetti

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Treatment Effect Estimation Using Invariant Risk Minimization.

[BibT_eX]

[DOI]

Abhin Shah

Kartik Ahuja

Karthikeyan Shanmugam

Proceedings of the IEEE International Conference on Acoustics, 2021

AI Explainability 360 Toolkit.

[BibT_eX]

[DOI]

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

2020

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

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2020

Optimal Policies for the Homogeneous Selective Labels Problem.

[BibT_eX]

[DOI]

CoRR, 2020

Consumer-Driven Explanations for Machine Learning Decisions: An Empirical Study of Robustness.

[BibT_eX]

[DOI]

Michael Hind

Yunfeng Zhang

CoRR, 2020

DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks.

[BibT_eX]

[DOI]

Tian Gao

Yue Yu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Model Projection: Theory and Applications to Fair Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2020

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

[BibT_eX]

[DOI]

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

AI explainability 360: hands-on tutorial.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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

Optimized Score Transformation for Fair Classification.

[BibT_eX]

[DOI]

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

Characterization of Overlap in Observational Studies.

[BibT_eX]

[DOI]

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

2019

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

[BibT_eX]

[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

Noel C. F. Codella

Michael Hind

CoRR, 2019

Generalized Linear Rule Models.

[BibT_eX]

[DOI]

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

TED: Teaching AI to Explain its Decisions.

[BibT_eX]

[DOI]

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

Fair Transfer Learning with Missing Protected Attributes.

[BibT_eX]

[DOI]

Amanda Coston

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

2018

Distribution-preserving k-anonymity.

[BibT_eX]

[DOI]

Stat. Anal. Data Min., 2018

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

[BibT_eX]

[DOI]

Flávio du Pin Calmon

Bhanukiran Vinzamuri

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

Teaching Meaningful Explanations.

[BibT_eX]

[DOI]

Noel C. F. Codella

Michael Hind

CoRR, 2018

Boolean Decision Rules via Column Generation.

[BibT_eX]

[DOI]

Sanjeeb Dash

Oktay Günlük

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Parallel Bayesian Network Structure Learning.

[BibT_eX]

[DOI]

Tian Gao

Proceedings of the 35th International Conference on Machine Learning, 2018

On the Supermodularity of Active Graph-Based Semi-Supervised Learning with Stieltjes Matrix Regularization.

[BibT_eX]

[DOI]

Pin-Yu Chen

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

k-quantiles: L1 distance clustering under a sum constraint.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2017

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

[BibT_eX]

[DOI]

CoRR, 2017

Optimized Data Pre-Processing for Discrimination Prevention.

[BibT_eX]

[DOI]

Flávio du Pin Calmon

CoRR, 2017

Optimized Pre-Processing for Discrimination Prevention.

[BibT_eX]

[DOI]

Bhanukiran Vinzamuri

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

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

[BibT_eX]

[DOI]

Jingwei Yang

Kevin N. Tran

Gigi Y. Yuen-Reed

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

2016

A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning sparse two-level boolean rules.

[BibT_eX]

[DOI]

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

Empirically-estimable multi-class classification bounds.

[BibT_eX]

[DOI]

Alan Wisler

Visar Berisha

Karthikeyan Ramamurthy

Andreas Spanias

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015

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

[BibT_eX]

[DOI]

ACM J. Data Inf. Qual., 2015

Interpretable Two-level Boolean Rule Learning for Classification.

[BibT_eX]

[DOI]

CoRR, 2015

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

[BibT_eX]

[DOI]

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

Toward Comprehensive Attribution of Healthcare Cost Changes.

[BibT_eX]

[DOI]

Gigi Y. Yuen-Reed

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

Robust binary hypothesis testing under contaminated likelihoods.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Adaptive sensing resource allocation over multiple hypothesis tests.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Optigrow: People Analytics for Job Transfers.

[BibT_eX]

[DOI]

Marcy Wagman

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

2014

Multiplicative regression via constrained least squares.

[BibT_eX]

[DOI]

Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

2013

Sparse Filter Design Under a Quadratic Constraint: Low-Complexity Algorithms.

[BibT_eX]

[DOI]

Charles K. Sestok

IEEE Trans. Signal Process., 2013

A Branch-and-Bound Algorithm for Quadratically-Constrained Sparse Filter Design.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2013

2011

Design of discrete-time filters for efficient implementation.

[BibT_eX]

[DOI]

PhD thesis, 2011

Saturation-robust SAR image formation.

[BibT_eX]

[DOI]

Petros Boufounos

Proceedings of the IEEE International Conference on Acoustics, 2011

2010

Linear programming algorithms for sparse filter design.

[BibT_eX]

[DOI]

Thomas A. Baran

IEEE Trans. Signal Process., 2010

Video stabilization and rolling shutter distortion reduction.

[BibT_eX]

[DOI]

Wei Hong

Aziz Umit Batur

Proceedings of the International Conference on Image Processing, 2010

Sparsity maximization under a quadratic constraint with applications in filter design.

[BibT_eX]

[DOI]