Dennis Wei - RankMe

132 papers A* 19A 9B 3C 3Misc 9Journal 71Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI Steerability 360: A Toolkit for Steering Large Language Models. CoRR Erik Miehling, Karthikeyan Natesan Ramamurthy, Praveen Venkateswaran, Irene Ko, Pierre L. Dognin, Moninder Singh, Tejaswini Pedapati, Avinash Balakrishnan, Matthew Riemer, Dennis Wei, Inge Vejsbjerg, Elizabeth M. Daly, Kush R. Varshney
2026	J	`jnl`	CoFrGeNet: Continued Fraction Architectures for Language Generation. CoRR Amit Dhurandhar, Vijil Chenthamarakshan, Dennis Wei, Tejaswini Pedapati, Karthikeyan Natesan Ramamurthy, Rahul Nair
2026	J	`jnl`	Entropy-Aware On-Policy Distillation of Language Models. CoRR Woogyeol Jin, Taywon Min, Yongjin Yang, Swanand Ravindra Kadhe, Yi Zhou, Dennis Wei, Nathalie Baracaldo, Kimin Lee
2026	A*	`conf`	Parameterized Abstract Interpretation for Transformer Verification. AAAI Pei Huang, Dennis Wei, Omri Isac, Haoze Wu, Min Wu, Clark W. Barrett
2025	J	`jnl`	Agentic AI Needs a Systems Theory. CoRR Erik Miehling, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Matthew Riemer, Djallel Bouneffouf, John T. Richards, Amit Dhurandhar, Elizabeth M. Daly, Michael Hind, Prasanna Sattigeri, Dennis Wei, Ambrish Rawat, Jasmina Gajcin, Werner Geyer
2025	J	`jnl`	CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions. CoRR Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Kartikeyan Shanmugam, Dennis Wei, Kush R. Varshney
2025	J	`jnl`	Dropping Just a Handful of Preferences Can Change Top Large Language Model Rankings. CoRR Jenny Y. Huang, Yunyi Shen, Dennis Wei, Tamara Broderick
2025	J	`jnl`	Highlight All the Phrases: Enhancing LLM Transparency through Visual Factuality Indicators. CoRR Hyo Jin Do, Rachel Ostrand, Werner Geyer, Keerthiram Murugesan, Dennis Wei, Justin D. Weisz
2025	J	`jnl`	ICX360: In-Context eXplainability 360 Toolkit. CoRR Dennis Wei, Ronny Luss, Xiaomeng Hu, Lucas Monteiro Paes, Pin-Yu Chen, Karthikeyan Natesan Ramamurthy, Erik Miehling, Inge Vejsbjerg, Hendrik Strobelt
2025	A*	`conf`	Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning. ICML Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning. CoRR Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu
2025	—	`conf`	LLM Unlearning on Noisy Forget Sets: A Study of Incomplete, Rewritten, and Watermarked Data. AISec@CCS Changsheng Wang, Yihua Zhang, Dennis Wei, Jinghan Jia, Pin-Yu Chen, Sijia Liu
2025	J	`jnl`	LLM Unlearning on Noisy Forget Sets: A Study of Incomplete, Rewritten, and Watermarked Data. CoRR Changsheng Wang, Yihua Zhang, Dennis Wei, Jinghan Jia, Pin-Yu Chen, Sijia Liu
2025	—	`conf`	Multi-Level Explanations for Generative Language Models. ACL (1) 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
2025	A*	`conf`	Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills. EMNLP Changsheng Wang, Chongyu Fan, Yihua Zhang, Jinghan Jia, Dennis Wei, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills. CoRR Changsheng Wang, Chongyu Fan, Yihua Zhang, Jinghan Jia, Dennis Wei, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers. Trans. Mach. Learn. Res. Hussein Mozannar, Valerie Chen, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David A. Sontag
2024	—	`conf`	Better Bias Benchmarking of Language Models via Multi-factor Analysis. AFME Hannah Powers, Ioana Baldini, Dennis Wei, Kristin P. Bennett
2024	A	`conf`	Causal Bandits with General Causal Models and Interventions. AISTATS Zirui Yan, Dennis Wei, Dmitriy A. Katz-Rogozhnikov, Prasanna Sattigeri, Ali Tajer
2024	J	`jnl`	Causal Bandits with General Causal Models and Interventions. CoRR Zirui Yan, Dennis Wei, Dmitriy A. Katz-Rogozhnikov, Prasanna Sattigeri, Ali Tajer
2024	J	`jnl`	Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations. CoRR 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
2024	J	`jnl`	Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions. CoRR Hyo Jin Do, Rachel Ostrand, Justin D. Weisz, Casey Dugan, Prasanna Sattigeri, Dennis Wei, Keerthiram Murugesan, Werner Geyer
2024	J	`jnl`	Final-Model-Only Data Attribution with a Unifying View of Gradient-Based Methods. CoRR Dennis Wei, Inkit Padhi, Soumya Ghosh, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Maria Chang
2024	J	`jnl`	Identifying Sub-networks in Neural Networks via Functionally Similar Representations. CoRR Tian Gao, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Dennis Wei
2024	A*	`conf`	Interventional Causal Discovery in a Mixture of DAGs. NeurIPS Burak Varici, Dmitriy Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer
2024	J	`jnl`	Interventional Causal Discovery in a Mixture of DAGs. CoRR Burak Varici, Dmitriy A. Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer
2024	J	`jnl`	Multi-Level Explanations for Generative Language Models. CoRR 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
2024	A*	`conf`	SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. ICLR Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu
2024	A*	`conf`	Selective Explanations. NeurIPS Lucas Monteiro Paes, Dennis Wei, Flávio P. Calmon
2024	J	`jnl`	Selective Explanations. CoRR Lucas Monteiro Paes, Dennis Wei, Flávio P. Calmon
2024	J	`jnl`	Separability Analysis for Causal Discovery in Mixture of DAGs. Trans. Mach. Learn. Res. Burak Varici, Dmitriy Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer
2024	J	`jnl`	Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs. CoRR Swanand Ravindra Kadhe, Farhan Ahmed, Dennis Wei, Nathalie Baracaldo, Inkit Padhi
2024	J	`jnl`	The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers. CoRR Hussein Mozannar, Valerie Chen, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David A. Sontag
2024	A*	`conf`	Trust Regions for Explanations via Black-Box Probabilistic Certification. ICML Amit Dhurandhar, Swagatam Haldar, Dennis Wei, Karthikeyan Natesan Ramamurthy
2024	J	`jnl`	Trust Regions for Explanations via Black-Box Probabilistic Certification. CoRR Amit Dhurandhar, Swagatam Haldar, Dennis Wei, Karthikeyan Natesan Ramamurthy
2024	A*	`conf`	Using Causal Inference to Investigate Contraceptive Discontinuation in Sub-Saharan Africa. IJCAI Victor Akinwande, Megan MacGregor, Celia Cintas, Ehud Karavani, Dennis Wei, Kush R. Varshney, Pablo A. Nepomnaschy
2023	Misc	`conf`	A Statistical Interpretation of the Maximum Subarray Problem. ICASSP Dennis Wei, Dmitry M. Malioutov
2023	—	`conf`	Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness. FAccT Brianna Richardson, Prasanna Sattigeri, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Amit Dhurandhar, Juan E. Gilbert
2023	B	`conf`	Adversarial Auditing of Machine Learning Models under Compound Shift. ESANN Karan Bhanot, Dennis Wei, Ioana Baldini, Kristin P. Bennett
2023	A	`conf`	Convex Bounds on the Softmax Function with Applications to Robustness Verification. AISTATS Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi
2023	J	`jnl`	Convex Bounds on the Softmax Function with Applications to Robustness Verification. CoRR Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi
2023	A*	`conf`	Effective Human-AI Teams via Learned Natural Language Rules and Onboarding. NeurIPS Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
2023	J	`jnl`	Effective Human-AI Teams via Learned Natural Language Rules and Onboarding. CoRR Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
2023	A	`conf`	Heavy Sets with Applications to Interpretable Machine Learning Diagnostics. AISTATS Dmitry M. Malioutov, Sanjeeb Dash, Dennis Wei
2023	J	`jnl`	Interpretable Differencing of Machine Learning Models. CoRR Swagatam Haldar, Diptikalyan Saha, Dennis Wei, Rahul Nair, Elizabeth M. Daly
2023	J	`jnl`	Interpretable and Fair Boolean Rule Sets via Column Generation. J. Mach. Learn. Res. Connor Lawless, Sanjeeb Dash, Oktay Günlük, Dennis Wei
2023	A	`conf`	Interpretable differencing of machine learning models. UAI Swagatam Haldar, Diptikalyan Saha, Dennis Wei, Rahul Nair, Elizabeth M. Daly
2023	J	`jnl`	SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. CoRR Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, Sijia Liu
2023	C	`conf`	Stress-Testing Bias Mitigation Algorithms to Understand Fairness Vulnerabilities. AIES Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng, Kristin P. Bennett
2023	A	`conf`	Who Should Predict? Exact Algorithms For Learning to Defer to Humans. AISTATS Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
2023	J	`jnl`	Who Should Predict? Exact Algorithms For Learning to Defer to Humans. CoRR Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
2022	A*	`conf`	AI Explainability 360: Impact and Design. AAAI 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
2022	J	`jnl`	Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners. CoRR Karthikeyan Natesan Ramamurthy, Amit Dhurandhar, Dennis Wei, Zaid Bin Tariq
2022	J	`jnl`	Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making. Proc. ACM Hum. Comput. Interact. Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, Richard Tomsett
2022	J	`jnl`	Downstream Fairness Caveats with Synthetic Healthcare Data. CoRR Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng, Kristin P. Bennett
2022	Misc	`conf`	Evaluating Fairness of Synthetic Healthcare Data Models. AMIA Karan Bhanot, Ioana Baldini, Dennis Wei, Jiaming Zeng, Kristin P. Bennett
2022	—	`conf`	FROTE: Feedback Rule-Driven Oversampling for Editing Models. MLSys Oznur Alkan, Dennis Wei, Massimiliano Mattetti, Rahul Nair, Elizabeth Daly, Diptikalyan Saha
2022	J	`jnl`	FROTE: Feedback Rule-Driven Oversampling for Editing Models. CoRR Öznur Alkan, Dennis Wei, Massimiliano Mattetti, Rahul Nair, Elizabeth M. Daly, Diptikalyan Saha
2022	A*	`conf`	On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach. NeurIPS Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney, Elizabeth Daly, Moninder Singh
2022	J	`jnl`	On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach. CoRR Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney, Elizabeth M. Daly, Moninder Singh
2022	—	`conf`	Your fairness may vary: Pretrained language model fairness in toxic text classification. ACL (Findings) Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh, Mikhail Yurochkin
2021	—	`conf`	AI Explainability 360 Toolkit. COMAD/CODS 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
2021	J	`jnl`	AI Explainability 360: Impact and Design. CoRR 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
2021	—	`conf`	AIMEE: Interactive model maintenance with rule-based surrogates. NeurIPS (Competition and Demos) Owen Cornec, Rahul Nair, Elizabeth Daly, Oznur Alkan, Dennis Wei
2021	A*	`conf`	CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions. NeurIPS Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney
2021	A	`conf`	Conditionally independent data generation. UAI Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu
2021	A*	`conf`	Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond. ICML Dennis Wei
2021	J	`jnl`	Ground-Truth, Whose Truth? - Examining the Challenges with Annotating Toxic Text Datasets. CoRR Kofi Arhin, Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh
2021	J	`jnl`	Interpretable and Fair Boolean Rule Sets via Column Generation. CoRR Connor Lawless, Sanjeeb Dash, Oktay Günlük, Dennis Wei
2021	J	`jnl`	Optimized Score Transformation for Consistent Fair Classification. J. Mach. Learn. Res. Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio P. Calmon
2021	Misc	`conf`	Treatment Effect Estimation Using Invariant Risk Minimization. ICASSP Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar
2021	J	`jnl`	Treatment Effect Estimation using Invariant Risk Minimization. CoRR Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar
2021	A*	`conf`	What Changed? Interpretable Model Comparison. IJCAI Rahul Nair, Massimiliano Mattetti, Elizabeth Daly, Dennis Wei, Oznur Alkan, Yunfeng Zhang
2021	J	`jnl`	Your fairness may vary: Group fairness of pretrained language models in toxic text classification. CoRR Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Mikhail Yurochkin, Moninder Singh
2020	J	`jnl`	AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models. J. Mach. Learn. Res. 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
2020	—	`conf`	AI explainability 360: hands-on tutorial. FAT* 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
2020	A	`conf`	Characterization of Overlap in Observational Studies. AISTATS Michael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel A. Brat, David A. Sontag, Kush R. Varshney
2020	J	`jnl`	Consumer-Driven Explanations for Machine Learning Decisions: An Empirical Study of Robustness. CoRR Michael Hind, Dennis Wei, Yunfeng Zhang
2020	A*	`conf`	DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks. NeurIPS Dennis Wei, Tian Gao, Yue Yu
2020	J	`jnl`	DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks. CoRR Dennis Wei, Tian Gao, Yue Yu
2020	J	`jnl`	Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making. CoRR Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, Richard Tomsett
2020	—	`conf`	Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines. CHIL Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney
2020	A*	`conf`	Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing. ICML Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney
2020	B	`conf`	Model Projection: Theory and Applications to Fair Machine Learning. ISIT Wael Alghamdi, Shahab Asoodeh, Hao Wang, Flávio P. Calmon, Dennis Wei, Karthikeyan Natesan Ramamurthy
2020	J	`jnl`	Optimal Policies for the Homogeneous Selective Labels Problem. CoRR Dennis Wei
2020	A	`conf`	Optimized Score Transformation for Fair Classification. AISTATS Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio P. Calmon
2019	J	`jnl`	An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy. CoRR Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney
2019	J	`jnl`	Characterization of Overlap in Observational Studies. CoRR Fredrik D. Johansson, Dennis Wei, Michael Oberst, Tian Gao, Gabriel A. Brat, David A. Sontag, Kush R. Varshney
2019	C	`conf`	Fair Transfer Learning with Missing Protected Attributes. AIES Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty
2019	A*	`conf`	Generalized Linear Rule Models. ICML Dennis Wei, Sanjeeb Dash, Tian Gao, Oktay Günlük
2019	J	`jnl`	Generalized Linear Rule Models. CoRR Dennis Wei, Sanjeeb Dash, Tian Gao, Oktay Günlük
2019	J	`jnl`	Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines. CoRR Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney
2019	J	`jnl`	One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques. CoRR 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
2019	J	`jnl`	Optimized Score Transformation for Fair Classification. CoRR Dennis Wei, Karthikeyan Natesan Ramamurthy, Flávio du Pin Calmon
2019	C	`conf`	TED: Teaching AI to Explain its Decisions. AIES Michael Hind, Dennis Wei, Murray Campbell, Noel C. F. Codella, Amit Dhurandhar, Aleksandra Mojsilovic, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
2019	J	`jnl`	Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning. CoRR Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic
2018	A*	`conf`	Boolean Decision Rules via Column Generation. NeurIPS Sanjeeb Dash, Oktay Günlük, Dennis Wei
2018	J	`jnl`	Boolean Decision Rules via Column Generation. CoRR Sanjeeb Dash, Oktay Günlük, Dennis Wei
2018	J	`jnl`	Data Pre-Processing for Discrimination Prevention: Information-Theoretic Optimization and Analysis. IEEE J. Sel. Top. Signal Process. Flávio du Pin Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
2018	J	`jnl`	Distribution-preserving k-anonymity. Stat. Anal. Data Min. Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
2018	Misc	`conf`	On the Supermodularity of Active Graph-Based Semi-Supervised Learning with Stieltjes Matrix Regularization. ICASSP Pin-Yu Chen, Dennis Wei
2018	J	`jnl`	On the Supermodularity of Active Graph-based Semi-supervised Learning with Stieltjes Matrix Regularization. CoRR Pin-Yu Chen, Dennis Wei
2018	A*	`conf`	Parallel Bayesian Network Structure Learning. ICML Tian Gao, Dennis Wei
2018	J	`jnl`	TED: Teaching AI to Explain its Decisions. CoRR Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic
2018	J	`jnl`	Teaching Meaningful Explanations. CoRR Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush R. Varshney, Dennis Wei, Aleksandra Mojsilovic
2017	—	`conf`	A configurable, big data system for on-demand healthcare cost prediction. IEEE BigData 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
2017	J	`jnl`	An End-To-End Machine Learning Pipeline That Ensures Fairness Policies. CoRR Samiulla Shaikh, Harit Vishwakarma, Sameep Mehta, Kush R. Varshney, Karthikeyan Natesan Ramamurthy, Dennis Wei
2017	J	`jnl`	Distribution-Preserving k-Anonymity. CoRR Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
2017	J	`jnl`	Optimized Data Pre-Processing for Discrimination Prevention. CoRR Flávio du Pin Calmon, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
2017	—	`conf`	Optimized Pre-Processing for Discrimination Prevention. NIPS Flávio P. Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
2017	J	`jnl`	k-quantiles: L1 distance clustering under a sum constraint. Pattern Recognit. Lett. Dennis Wei
2016	J	`jnl`	A Constant-Factor Bi-Criteria Approximation Guarantee for $k$-means++. CoRR Dennis Wei
2016	—	`conf`	A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++. NIPS Dennis Wei
2016	Misc	`conf`	Empirically-estimable multi-class classification bounds. ICASSP Alan Wisler, Visar Berisha, Dennis Wei, Karthikeyan Ramamurthy, Andreas Spanias
2016	J	`jnl`	Interpretable Two-level Boolean Rule Learning for Classification. CoRR Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov
2016	—	`conf`	Learning sparse two-level boolean rules. MLSP Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov
2015	Misc	`conf`	Adaptive sensing resource allocation over multiple hypothesis tests. ICASSP Dennis Wei
2015	J	`jnl`	Data Challenges in Disease Response: The 2014 Ebola Outbreak and Beyond. ACM J. Data Inf. Qual. Kush R. Varshney, Dennis Wei, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic
2015	A	`conf`	Health Insurance Market Risk Assessment: Covariate Shift and k-Anonymity. SDM Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
2015	J	`jnl`	Interpretable Two-level Boolean Rule Learning for Classification. CoRR Guolong Su, Dennis Wei, Kush R. Varshney, Dmitry M. Malioutov
2015	—	`conf`	Optigrow: People Analytics for Job Transfers. BigData Congress Dennis Wei, Kush R. Varshney, Marcy Wagman
2015	Misc	`conf`	Robust binary hypothesis testing under contaminated likelihoods. ICASSP Dennis Wei, Kush R. Varshney
2015	—	`conf`	Toward Comprehensive Attribution of Healthcare Cost Changes. ICDM Workshops Dmitriy A. Katz-Rogozhnikov, Dennis Wei, Gigi Y. Yuen-Reed, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic
2014	—	`conf`	Multiplicative regression via constrained least squares. SSP Dennis Wei, Karthikeyan Natesan Ramamurthy, Dmitriy A. Katz-Rogozhnikov, Aleksandra Mojsilovic
2014	J	`jnl`	Robust Binary Hypothesis Testing Under Contaminated Likelihoods. CoRR Dennis Wei, Kush R. Varshney
2013	J	`jnl`	A Branch-and-Bound Algorithm for Quadratically-Constrained Sparse Filter Design. IEEE Trans. Signal Process. Dennis Wei, Alan V. Oppenheim
2013	J	`jnl`	Sparse Filter Design Under a Quadratic Constraint: Low-Complexity Algorithms. IEEE Trans. Signal Process. Dennis Wei, Charles K. Sestok, Alan V. Oppenheim
2011	—	`—`	Design of discrete-time filters for efficient implementation. Dennis Wei
2011	Misc	`conf`	Saturation-robust SAR image formation. ICASSP Dennis Wei, Petros Boufounos
2010	J	`jnl`	Linear programming algorithms for sparse filter design. IEEE Trans. Signal Process. Thomas A. Baran, Dennis Wei, Alan V. Oppenheim
2010	Misc	`conf`	Sparsity maximization under a quadratic constraint with applications in filter design. ICASSP Dennis Wei, Alan V. Oppenheim
2010	B	`conf`	Video stabilization and rolling shutter distortion reduction. ICIP Wei Hong, Dennis Wei, Aziz Umit Batur