Dennis Wei

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 99

Top Venues

Massachusetts Institute of Technology, Cambridge, MA, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, MA, USA

PHD

Publications

Swanand Ravindra Kadhe, Farhan Ahmed, Dennis Wei, Nathalie Baracaldo, Inkit Padhi
Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs. CoRR (2024)
Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. ICLR (2024)
Hyo Jin Do, Rachel Ostrand, Justin D. Weisz, Casey Dugan, Prasanna Sattigeri, Dennis Wei, Keerthiram Murugesan, Werner Geyer
Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions. CoRR (2024)
Zirui Yan, Dennis Wei, Dmitriy A. Katz-Rogozhnikov, Prasanna Sattigeri, Ali Tajer
Causal Bandits with General Causal Models and Interventions. CoRR (2024)
Burak Varici, Dmitriy Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer
Separability Analysis for Causal Discovery in Mixture of DAGs. Trans. Mach. Learn. Res. 2024 (2024)
Zirui Yan, Dennis Wei, Dmitriy A. Katz, Prasanna Sattigeri, Ali Tajer
Causal Bandits with General Causal Models and Interventions. AISTATS (2024)
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
Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations. CoRR (2024)
Lucas Monteiro Paes, Dennis Wei, Hyo Jin Do, Hendrik Strobelt, Ronny Luss, Amit Dhurandhar, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Werner Geyer, Soumya Ghosh
Multi-Level Explanations for Generative Language Models. CoRR (2024)
Amit Dhurandhar, Swagatam Haldar, Dennis Wei, Karthikeyan Natesan Ramamurthy
Trust Regions for Explanations via Black-Box Probabilistic Certification. CoRR (2024)
Burak Varici, Dmitriy A. Katz-Rogozhnikov, Dennis Wei, Prasanna Sattigeri, Ali Tajer
Interventional Causal Discovery in a Mixture of DAGs. CoRR (2024)
Hussein Mozannar, Valerie Chen, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David A. Sontag
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers. CoRR (2024)
Lucas Monteiro Paes, Dennis Wei, Flávio P. Calmon
Selective Explanations. CoRR (2024)
Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi
Convex Bounds on the Softmax Function with Applications to Robustness Verification. CoRR (2023)
Swagatam Haldar, Diptikalyan Saha, Dennis Wei, Rahul Nair, Elizabeth M. Daly
Interpretable differencing of machine learning models. UAI (2023)
Dennis Wei, Dmitry M. Malioutov
A Statistical Interpretation of the Maximum Subarray Problem. ICASSP (2023)
Connor Lawless, Sanjeeb Dash, Oktay Günlük, Dennis Wei
Interpretable and Fair Boolean Rule Sets via Column Generation. J. Mach. Learn. Res. 24 (2023)
Swagatam Haldar, Diptikalyan Saha, Dennis Wei, Rahul Nair, Elizabeth M. Daly
Interpretable Differencing of Machine Learning Models. CoRR (2023)
Karan Bhanot, Dennis Wei, Ioana Baldini, Kristin P. Bennett
Adversarial Auditing of Machine Learning Models under Compound Shift. ESANN (2023)
Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi
Convex Bounds on the Softmax Function with Applications to Robustness Verification. AISTATS (2023)
Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding. NeurIPS (2023)
Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng, Kristin P. Bennett
Stress-Testing Bias Mitigation Algorithms to Understand Fairness Vulnerabilities. AIES (2023)
Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
Who Should Predict? Exact Algorithms For Learning to Defer to Humans. CoRR (2023)
Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
Who Should Predict? Exact Algorithms For Learning to Defer to Humans. AISTATS (2023)
Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, Sijia Liu
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. CoRR (2023)
Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding. CoRR (2023)
Dmitry M. Malioutov, Sanjeeb Dash, Dennis Wei
Heavy Sets with Applications to Interpretable Machine Learning Diagnostics. AISTATS (2023)
Brianna Richardson, Prasanna Sattigeri, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush Varshney, Amit Dhurandhar, Juan E. Gilbert
Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness. FAccT (2023)
Oznur Alkan, Dennis Wei, Massimiliano Mattetti, Rahul Nair, Elizabeth Daly, Diptikalyan Saha
FROTE: Feedback Rule-Driven Oversampling for Editing Models. MLSys (2022)
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 (2022)
Karthikeyan Natesan Ramamurthy, Amit Dhurandhar, Dennis Wei, Zaid Bin Tariq
Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners. CoRR (2022)
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)
Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng, Kristin P. Bennett
Evaluating Fairness of Synthetic Healthcare Data Models. AMIA (2022)
Öznur Alkan, Dennis Wei, Massimiliano Mattetti, Rahul Nair, Elizabeth M. Daly, Diptikalyan Saha
FROTE: Feedback Rule-Driven Oversampling for Editing Models. CoRR (2022)
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)
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)
Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng, Kristin P. Bennett
Downstream Fairness Caveats with Synthetic Healthcare Data. CoRR (2022)
Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, Richard Tomsett
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making. Proc. ACM Hum. Comput. Interact. 6 (CSCW1) (2022)
Owen Cornec, Rahul Nair, Elizabeth Daly, Oznur Alkan, Dennis Wei
AIMEE: Interactive model maintenance with rule-based surrogates. NeurIPS (Competition and Demos) (2021)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio du Pin Calmon
Optimized Score Transformation for Consistent Fair Classification. J. Mach. Learn. Res. 22 (2021)
Kofi Arhin, Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh
Ground-Truth, Whose Truth? - Examining the Challenges with Annotating Toxic Text Datasets. CoRR (2021)
Connor Lawless, Sanjeeb Dash, Oktay Günlük, Dennis Wei
Interpretable and Fair Boolean Rule Sets via Column Generation. CoRR (2021)
Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar
Treatment Effect Estimation using Invariant Risk Minimization. CoRR (2021)
Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu
Conditionally independent data generation. UAI (2021)
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)
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 (2021)
Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar
Treatment Effect Estimation Using Invariant Risk Minimization. ICASSP (2021)
Rahul Nair, Massimiliano Mattetti, Elizabeth Daly, Dennis Wei, Oznur Alkan, Yunfeng Zhang
What Changed? Interpretable Model Comparison. IJCAI (2021)
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 (2021)
Dennis Wei
Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond. ICML (2021)
Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney
CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions. NeurIPS (2021)
Dennis Wei
Optimal Policies for the Homogeneous Selective Labels Problem. CoRR (2020)
Dennis Wei, Tian Gao, Yue Yu
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks. NeurIPS (2020)
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 (2020)
Michael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel Brat, David A. Sontag, Kush R. Varshney
Characterization of Overlap in Observational Studies. AISTATS (2020)
Michael Hind, Dennis Wei, Yunfeng Zhang
Consumer-Driven Explanations for Machine Learning Decisions: An Empirical Study of Robustness. CoRR (2020)
Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney
Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines. CHIL (2020)
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)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio du Pin Calmon
Optimized Score Transformation for Fair Classification. AISTATS (2020)
Dennis Wei, Tian Gao, Yue Yu
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks. CoRR (2020)
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing. ICML (2020)
Wael Alghamdi, Shahab Asoodeh, Hao Wang, Flávio P. Calmon, Dennis Wei, Karthikeyan Natesan Ramamurthy
Model Projection: Theory and Applications to Fair Machine Learning. ISIT (2020)
Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, Richard Tomsett
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making. CoRR (2020)
Michael Hind, Dennis Wei, Murray Campbell, Noel C. F. Codella, Amit Dhurandhar, Aleksandra Mojsilovic, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
TED: Teaching AI to Explain its Decisions. AIES (2019)
Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney
Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines. CoRR (2019)
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney
An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy. CoRR (2019)
Dennis Wei, Sanjeeb Dash, Tian Gao, Oktay Günlük
Generalized Linear Rule Models. ICML (2019)
Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty
Fair Transfer Learning with Missing Protected Attributes. AIES (2019)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio du Pin Calmon
Optimized Score Transformation for Fair Classification. CoRR (2019)
Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic
Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning. CoRR (2019)
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 (2019)
Dennis Wei, Sanjeeb Dash, Tian Gao, Oktay Günlük
Generalized Linear Rule Models. CoRR (2019)
Fredrik D. Johansson, Dennis Wei, Michael Oberst, Tian Gao, Gabriel Brat, David A. Sontag, Kush R. Varshney
Characterization of Overlap in Observational Studies. CoRR (2019)
Flávio du Pin Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Data Pre-Processing for Discrimination Prevention: Information-Theoretic Optimization and Analysis. IEEE J. Sel. Top. Signal Process. 12 (5) (2018)
Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic
TED: Teaching AI to Explain its Decisions. CoRR (2018)
Pin-Yu Chen, Dennis Wei
On the Supermodularity of Active Graph-Based Semi-Supervised Learning with Stieltjes Matrix Regularization. ICASSP (2018)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Distribution-preserving k-anonymity. Stat. Anal. Data Min. 11 (6) (2018)
Sanjeeb Dash, Oktay Günlük, Dennis Wei
Boolean Decision Rules via Column Generation. NeurIPS (2018)
Sanjeeb Dash, Oktay Günlük, Dennis Wei
Boolean Decision Rules via Column Generation. CoRR (2018)
Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic
Teaching Meaningful Explanations. CoRR (2018)
Pin-Yu Chen, Dennis Wei
On the Supermodularity of Active Graph-based Semi-supervised Learning with Stieltjes Matrix Regularization. CoRR (2018)
Tian Gao, Dennis Wei
Parallel Bayesian Network Structure Learning. ICML (2018)
Samiulla Shaikh, Harit Vishwakarma, Sameep Mehta, Kush R. Varshney, Karthikeyan Natesan Ramamurthy, Dennis Wei
An End-To-End Machine Learning Pipeline That Ensures Fairness Policies. CoRR (2017)
Dennis Wei
k-quantiles: L1 distance clustering under a sum constraint. Pattern Recognit. Lett. 92 (2017)
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)
Flávio du Pin Calmon, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Optimized Data Pre-Processing for Discrimination Prevention. CoRR (2017)
Flávio du Pin Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Optimized Pre-Processing for Discrimination Prevention. NIPS (2017)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Distribution-Preserving k-Anonymity. CoRR (2017)
Dennis Wei
A Constant-Factor Bi-Criteria Approximation Guarantee for $k$-means++. CoRR (2016)
Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov
Interpretable Two-level Boolean Rule Learning for Classification. CoRR (2016)
Dennis Wei
A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++. NIPS (2016)
Alan Wisler, Visar Berisha, Dennis Wei, Karthikeyan Ramamurthy, Andreas Spanias
Empirically-estimable multi-class classification bounds. ICASSP (2016)
Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov
Learning sparse two-level boolean rules. MLSP (2016)
Dmitriy A. Katz-Rogozhnikov, Dennis Wei, Gigi Y. Yuen-Reed, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic
Toward Comprehensive Attribution of Healthcare Cost Changes. ICDM Workshops (2015)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
Health Insurance Market Risk Assessment: Covariate Shift and k-Anonymity. SDM (2015)
Dennis Wei
Adaptive sensing resource allocation over multiple hypothesis tests. ICASSP (2015)
Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov
Interpretable Two-level Boolean Rule Learning for Classification. CoRR (2015)
Kush R. Varshney, Dennis Wei, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic
Data Challenges in Disease Response: The 2014 Ebola Outbreak and Beyond. ACM J. Data Inf. Qual. 6 (2-3) (2015)
Dennis Wei, Kush R. Varshney, Marcy Wagman
Optigrow: People Analytics for Job Transfers. BigData Congress (2015)
Dennis Wei, Kush R. Varshney
Robust binary hypothesis testing under contaminated likelihoods. ICASSP (2015)
Dennis Wei, Karthikeyan Natesan Ramamurthy, Dmitriy A. Katz-Rogozhnikov, Aleksandra Mojsilovic
Multiplicative regression via constrained least squares. SSP (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Dennis Wei