Finale Doshi-Velez

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 201

Top Venues

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

Education History

Massachusetts Institute of Technology, Cambridge, MA, USA

PHD

Publications

Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. AAMAS (2024)
Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. CoRR (2024)
Tom Zick, Mason Kortz, David Eaves, Finale Doshi-Velez
AI Procurement Checklists: Revisiting Implementation in the Age of AI Governance. CoRR (2024)
Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez
Guarantee Regions for Local Explanations. CoRR (2024)
Siddharth Swaroop, Zana Buçinca, Krzysztof Z. Gajos, Finale Doshi-Velez
Accuracy-Time Tradeoffs in AI-Assisted Decision Making under Time Pressure. IUI (2024)
Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Iris Yan, Finale Doshi-Velez, Susan A. Murphy
Monitoring Fidelity of Online Reinforcement Learning Algorithms in Clinical Trials. CoRR (2024)
Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez
Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. Tiny Papers @ ICLR (2024)
Abhishek Sharma, Catherine Zeng, Sanjana Narayanan, Sonali Parbhoo, Roy H. Perlis, Finale Doshi-Velez
Task-Relevant Feature Selection with Prediction Focused Mixture Models. Trans. Mach. Learn. Res. 2024 (2024)
Yidou Weng, Finale Doshi-Velez
Semi-parametric Expert Bayesian Network Learning with Gaussian Processes and Horseshoe Priors. CoRR (2024)
Anna L. Trella, Walter Dempsey, Finale Doshi-Velez, Susan A. Murphy
Non-Stationary Latent Auto-Regressive Bandits. CoRR (2024)
Isaac Lage, Sonali Parbhoo, Finale Doshi-Velez
Towards Integrating Personal Knowledge into Test-Time Predictions. CoRR (2024)
Ze Yu Zhang, Arun Verma, Finale Doshi-Velez, Bryan Kian Hsiang Low
Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models. CoRR (2024)
Eura Nofshin, Esther Brown, Brian Lim, Weiwei Pan, Finale Doshi-Velez
A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning. CoRR (2024)
Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders. CoRR (2024)
Varshini Subhash, Anna Bialas, Weiwei Pan, Finale Doshi-Velez
Why do universal adversarial attacks work on large language models?: Geometry might be the answer. CoRR (2023)
Xudong Shen, Hannah Brown, Jiashu Tao, Martin Strobel, Yao Tong, Akshay Narayan, Harold Soh, Finale Doshi-Velez
Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities. CoRR (2023)
Haotian Fu, Jiayu Yao, Omer Gottesman, Finale Doshi-Velez, George Konidaris
Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs. ICLR (2023)
Sarah Rathnam, Sonali Parbhoo, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning. ICML (2023)
Abhishek Sharma, Sonali Parbhoo, Omer Gottesman, Finale Doshi-Velez
Robust Decision-Focused Learning for Reward Transfer. CoRR (2023)
Shengpu Tang, Maggie Makar, Michael W. Sjoding, Finale Doshi-Velez, Jenna Wiens
Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare. CoRR (2023)
Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez
Learning-to-defer for sequential medical decision-making under uncertainty. Trans. Mach. Learn. Res. 2023 (2023)
Eura Shin, Predrag Klasnja, Susan A. Murphy, Finale Doshi-Velez
Online model selection by learning how compositional kernels evolve. Trans. Mach. Learn. Res. 2023 (2023)
Abhishek Sharma, Jing Zhang, Daniel Nikovski, Finale Doshi-Velez
Travel-time prediction using neural-network-based mixture models. ANT/EDI40 (2023)
Lars Lien Ankile, Brian S. Ham, Kevin Mao, Eura Shin, Siddharth Swaroop, Finale Doshi-Velez, Weiwei Pan
Discovering User Types: Mapping User Traits by Task-Specific Behaviors in Reinforcement Learning. CoRR (2023)
Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
Reward Design for an Online Reinforcement Learning Algorithm Supporting Oral Self-Care. AAAI (2023)
Leo Benac, Sonali Parbhoo, Finale Doshi-Velez
Bayesian Inverse Transition Learning for Offline Settings. CoRR (2023)
Siddharth Swaroop, Zana Buçinca, Finale Doshi-Velez
Adaptive interventions for both accuracy and time in AI-assisted human decision making. CoRR (2023)
Sarah Rathnam, Sonali Parbhoo, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning. CoRR (2023)
Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez
Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. CoRR (2023)
José Roberto Tello-Ayala, Akl C. Fahed, Weiwei Pan, Eugene V. Pomerantsev, Patrick T. Ellinor, Anthony Philippakis, Finale Doshi-Velez
Signature Activation: A Sparse Signal View for Holistic Saliency. CoRR (2023)
Yiqing Xu, Finale Doshi-Velez, David Hsu
On the Effective Horizon of Inverse Reinforcement Learning. CoRR (2023)
Charumathi Badrinath, Weiwei Pan, Finale Doshi-Velez
SAP-sLDA: An Interpretable Interface for Exploring Unstructured Text. CoRR (2023)
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
Towards Robust Off-Policy Evaluation via Human Inputs. AIES (2022)
Jiayu Yao, Yaniv Yacoby, Beau Coker, Weiwei Pan, Finale Doshi-Velez
An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks. CoRR (2022)
Sanjana Narayanan, Isaac Lage, Finale Doshi-Velez
(When) Are Contrastive Explanations of Reinforcement Learning Helpful? CoRR (2022)
Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez
Addressing Leakage in Concept Bottleneck Models. NeurIPS (2022)
Sonali Parbhoo, Shalmali Joshi, Finale Doshi-Velez
Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making. CoRR (2022)
Kelly W. Zhang, Omer Gottesman, Finale Doshi-Velez
A Bayesian Approach to Learning Bandit Structure in Markov Decision Processes. CoRR (2022)
Q. Vera Liao, Yunfeng Zhang, Ronny Luss, Finale Doshi-Velez, Amit Dhurandhar
Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI. CoRR (2022)
Mark Penrod, Harrison Termotto, Varshini Reddy, Jiayu Yao, Finale Doshi-Velez, Weiwei Pan
Success of Uncertainty-Aware Deep Models Depends on Data Manifold Geometry. CoRR (2022)
Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care. CoRR (2022)
Jiayu Yao, Sonali Parbhoo, Weiwei Pan, Finale Doshi-Velez
Policy Optimization with Sparse Global Contrastive Explanations. CoRR (2022)
Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-implementation Guidelines. CoRR (2022)
Zixi Chen, Varshini Subhash, Marton Havasi, Weiwei Pan, Finale Doshi-Velez
Does the explanation satisfy your needs?: A unified view of properties of explanations. CoRR (2022)
Michael L. Littman, Ifeoma Ajunwa, Guy Berger, Craig Boutilier, Morgan Currie, Finale Doshi-Velez, Gillian K. Hadfield, Michael C. Horowitz, Charles Isbell, Hiroaki Kitano, Karen Levy, Terah Lyons, Melanie Mitchell, Julie Shah, Steven Sloman, Shannon Vallor, Toby Walsh
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. CoRR (2022)
Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines. Algorithms 15 (8) (2022)
Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez
Wide Mean-Field Bayesian Neural Networks Ignore the Data. CoRR (2022)
Shengpu Tang, Maggie Makar, Michael W. Sjoding, Finale Doshi-Velez, Jenna Wiens
Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare. NeurIPS (2022)
Jeffrey Chiu, Rajat Mittal, Neehal Tumma, Abhishek Sharma, Finale Doshi-Velez
A Joint Learning Approach for Semi-supervised Neural Topic Modeling. SPNLP@ACL (2022)
Carissa Wu, Sonali Parbhoo, Marton Havasi, Finale Doshi-Velez
Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models. MLHC (2022)
Eura Shin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
Modeling Mobile Health Users as Reinforcement Learning Agents. CoRR (2022)
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
Towards Robust Off-Policy Evaluation via Human Inputs. CoRR (2022)
Jeffrey Chiu, Rajat Mittal, Neehal Tumma, Abhishek Sharma, Finale Doshi-Velez
A Joint Learning Approach for Semi-supervised Neural Topic Modeling. CoRR (2022)
Yaniv Yacoby, Ben Green, Christopher L. Griffin, Finale Doshi-Velez
"If it didn't happen, why would I change my decision?": How Judges Respond to Counterfactual Explanations for the Public Safety Assessment. CoRR (2022)
Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez
Wide Mean-Field Bayesian Neural Networks Ignore the Data. AISTATS (2022)
Q. Vera Liao, Yunfeng Zhang, Ronny Luss, Finale Doshi-Velez, Amit Dhurandhar
Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI. HCOMP (2022)
Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables. J. Mach. Learn. Res. 23 (2022)
Yaniv Yacoby, Ben Green, Christopher L. Griffin, Finale Doshi-Velez
"If it didn't happen, why would I change my decision?": How Judges Respond to Counterfactual Explanations for the Public Safety Assessment. HCOMP (2022)
Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill
Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation. CHIL (2022)
Kristine Zhang, Henry Wang, Jianzhun Du, Brian Chu, Aldo Arévalo, Ryan Kindle, Leo Anthony Celi, Finale Doshi-Velez
An interpretable RL framework for pre-deployment modeling in ICU hypotension management. npj Digit. Medicine 5 (2022)
Maia Jacobs, Jeffrey He, Melanie F. Pradier, Barbara Lam, Andrew C. Ahn, Thomas H. McCoy, Roy H. Perlis, Finale Doshi-Velez, Krzysztof Z. Gajos
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens. CHI (2021)
Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill
Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation. CoRR (2021)
Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez
State Relevance for Off-Policy Evaluation. CoRR (2021)
Nari Johnson, Sonali Parbhoo, Andrew Slavin Ross, Finale Doshi-Velez
Learning Predictive and Interpretable Timeseries Summaries from ICU Data. AMIA (2021)
Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning. CoRR (2021)
Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning. NeurIPS (2021)
Abhishek Sharma, Catherine Zeng, Sanjana Narayanan, Sonali Parbhoo, Finale Doshi-Velez
On Learning Prediction-Focused Mixtures. CoRR (2021)
Lifeng Jin, Lane Schwartz, Finale Doshi-Velez, Timothy A. Miller, William Schuler
Depth-Bounded Statistical PCFG Induction as a Model of Human Grammar Acquisition. Comput. Linguistics 47 (1) (2021)
Kristine Zhang, Yuanheng Wang, Jianzhun Du, Brian Chu, Leo Anthony Celi, Ryan Kindle, Finale Doshi-Velez
Identifying Decision Points for Safe and Interpretable Reinforcement Learning in Hypotension Treatment. CoRR (2021)
Andrew Slavin Ross, Finale Doshi-Velez
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement. ICML (2021)
Anita Mahinpei, Justin Clark, Isaac Lage, Finale Doshi-Velez, Weiwei Pan
Promises and Pitfalls of Black-Box Concept Learning Models. CoRR (2021)
Melanie F. Pradier, Javier Zazo, Sonali Parbhoo, Roy H. Perlis, Maurizio Zazzi, Finale Doshi-Velez
Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible. CoRR (2021)
Andrew Slavin Ross, Nina Chen, Elisa Zhao Hang, Elena L. Glassman, Finale Doshi-Velez
Evaluating the Interpretability of Generative Models by Interactive Reconstruction. CHI (2021)
Sarah Rathnam, Susan A. Murphy, Finale Doshi-Velez
Comparison and Unification of Three Regularization Methods in Batch Reinforcement Learning. CoRR (2021)
Beau Coker, Weiwei Pan, Finale Doshi-Velez
Wide Mean-Field Variational Bayesian Neural Networks Ignore the Data. CoRR (2021)
Andrew Slavin Ross, Finale Doshi-Velez
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement. CoRR (2021)
Andrew Slavin Ross, Nina Chen, Elisa Zhao Hang, Elena L. Glassman, Finale Doshi-Velez
Evaluating the Interpretability of Generative Models by Interactive Reconstruction. CoRR (2021)
Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez
Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty. CoRR (2021)
Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
Power Constrained Bandits. MLHC (2021)
Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez
State Relevance for Off-Policy Evaluation. ICML (2021)
Been Kim, Finale Doshi-Velez
Machine Learning Techniques for Accountability. AI Mag. 42 (1) (2021)
Nari Johnson, Sonali Parbhoo, Andrew Slavin Ross, Finale Doshi-Velez
Learning Predictive and Interpretable Timeseries Summaries from ICU Data. CoRR (2021)
Tianyi Zhang, Thomas H. McCoy, Roy H. Perlis, Finale Doshi-Velez, Elena L. Glassman
Interactive Cohort Analysis and Hypothesis Discovery by Exploring Temporal Patterns in Population-Level Health Records. VAHC (2021)
Eura Shin, Pedja Klasnja, Susan A. Murphy, Finale Doshi-Velez
Online structural kernel selection for mobile health. CoRR (2021)
Mike Wu, Sonali Parbhoo, Michael C. Hughes, Volker Roth, Finale Doshi-Velez
Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. J. Artif. Intell. Res. 72 (2021)
Maia Jacobs, Jeffrey He, Melanie F. Pradier, Barbara Lam, Andrew C. Ahn, Thomas H. McCoy, Roy H. Perlis, Finale Doshi-Velez, Krzysztof Z. Gajos
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens. CoRR (2021)
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
Learning Under Adversarial and Interventional Shifts. CoRR (2021)
Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks. CoRR (2020)
Isaac Lage, Finale Doshi-Velez
Learning Interpretable Concept-Based Models with Human Feedback. CoRR (2020)
Joseph Futoma, Michael C. Hughes, Finale Doshi-Velez
POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning. CoRR (2020)
Wanqian Yang, Lars Lorch, Moritz A. Graule, Himabindu Lakkaraju, Finale Doshi-Velez
Incorporating Interpretable Output Constraints in Bayesian Neural Networks. CoRR (2020)
Sujay Thakur, Cooper Lorsung, Yaniv Yacoby, Finale Doshi-Velez, Weiwei Pan
Learned Uncertainty-Aware (LUNA) Bases for Bayesian Regression using Multi-Headed Auxiliary Networks. CoRR (2020)
Niranjani Prasad, Barbara E. Engelhardt, Finale Doshi-Velez
Defining admissible rewards for high-confidence policy evaluation in batch reinforcement learning. CHIL (2020)
Andrew Slavin Ross, Weiwei Pan, Leo A. Celi, Finale Doshi-Velez
Ensembles of Locally Independent Prediction Models. AAAI (2020)
Jianzhun Du, Joseph Futoma, Finale Doshi-Velez
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs. NeurIPS (2020)
Elisa Bertino, Finale Doshi-Velez, Maria L. Gini, Daniel Lopresti, David Parkes
Artificial Intelligence & Cooperation. CoRR (2020)
Joseph Futoma, Michael C. Hughes, Finale Doshi-Velez
POPCORN: Partially Observed Prediction Constrained Reinforcement Learning. AISTATS (2020)
Beau Coker, Melanie Fernandes Pradier, Finale Doshi-Velez
PoRB-Nets: Poisson Process Radial Basis Function Networks. UAI (2020)
Mike Wu, Sonali Parbhoo, Michael C. Hughes, Ryan Kindle, Leo A. Celi, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
Regional Tree Regularization for Interpretability in Deep Neural Networks. AAAI (2020)
Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
Power-Constrained Bandits. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Finale Doshi-Velez