Finale Doshi-Velez

257 papers A* 40A 17B 5C 2Misc 3Journal 159Unranked 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Benchmark for Multi-Party Negotiation Games from Real Negotiation Data. CoRR Leo Benac, Jonas Raedler, Zilin Ma, Finale Doshi-Velez
2026	J	`jnl`	A Benchmark to Assess Common Ground in Human-AI Collaboration. CoRR Christian Pölitz, Finale Doshi-Velez, Siân Lindley
2026	J	`jnl`	Shaping AI's Impact on Billions of Lives. Commun. ACM Mariano-Florentino Cuellar, Jeff Dean, Finale Doshi-Velez, John L. Hennessy, Andy Konwinski, Sanmi Koyejo, Pelonomi Moiloa, Emma Pierson, David A. Patterson
2025	A*	`conf`	A Deployed Online Reinforcement Learning Algorithm in an Oral Health Clinical Trial. AAAI Anna L. Trella, Kelly W. Zhang, Hinal Jajal, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
2025	A*	`conf`	Connecting Federated ADMM to Bayes. ICLR Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez
2025	J	`jnl`	Connecting Federated ADMM to Bayes. CoRR Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez
2025	A*	`conf`	Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills. CHI Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch, Finale Doshi-Velez, Krzysztof Z. Gajos
2025	A	`conf`	Decision-Point Guided Safe Policy Improvement. AISTATS Abhishek Sharma, Leo Benac, Sonali Parbhoo, Finale Doshi-Velez
2025	J	`jnl`	Estimating Upper Extremity Fugl-Meyer Assessment Scores From Reaching Motions Using Wearable Sensors. IEEE J. Biomed. Health Informatics Yu Meng Zhou, Nihal Raman, Tommaso Proietti, James Arnold, Prabhat Pathak, David Pont-Esteban, Kristin Nuckols, Kelly Rishe, Finale Doshi-Velez, David J. Lin, Conor J. Walsh
2025	J	`jnl`	Federated ADMM from Bayesian Duality. CoRR Thomas Möllenhoff, Siddharth Swaroop, Finale Doshi-Velez, Mohammad Emtiyaz Khan
2025	A	`conf`	On the Effective Horizon of Inverse Reinforcement Learning. AAMAS Yiqing Xu, Finale Doshi-Velez, David Hsu
2025	A	`conf`	Personalising AI Assistance Based on Overreliance Rate in AI-Assisted Decision Making. IUI Siddharth Swaroop, Zana Buçinca, Krzysztof Z. Gajos, Finale Doshi-Velez
2025	J	`jnl`	Strategically Linked Decisions in Long-Term Planning and Reinforcement Learning. CoRR Alihan Hüyük, Finale Doshi-Velez
2025	A	`conf`	Transparent Trade-offs between Properties of Explanations. UAI Hiwot Belay Tadesse, Alihan Hüyük, Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
2025	—	`conf`	User Studies in Human-Feature-Integration. IUI Workshops Yixin Li, Lucas Lefebvre, Sonali Parbhoo, Finale Doshi-Velez, Isaac Lage
2024	J	`jnl`	A Deployed Online Reinforcement Learning Algorithm In An Oral Health Clinical Trial. CoRR Anna L. Trella, Kelly W. Zhang, Hinal Jajal, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
2024	J	`jnl`	A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning. CoRR Eura Nofshin, Esther Brown, Brian Lim, Weiwei Pan, Finale Doshi-Velez
2024	J	`jnl`	AI Procurement Checklists: Revisiting Implementation in the Age of AI Governance. CoRR Tom Zick, Mason Kortz, David Eaves, Finale Doshi-Velez
2024	A	`conf`	Accuracy-Time Tradeoffs in AI-Assisted Decision Making under Time Pressure. IUI Siddharth Swaroop, Zana Buçinca, Krzysztof Z. Gajos, Finale Doshi-Velez
2024	J	`jnl`	Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills. CoRR Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch, Finale Doshi-Velez, Krzysztof Z. Gajos
2024	—	`conf`	Decision-Focused Model-based Reinforcement Learning for Reward Transfer. MLHC Abhishek Sharma, Sonali Parbhoo, Omer Gottesman, Finale Doshi-Velez
2024	J	`jnl`	Decision-Point Guided Safe Policy Improvement. CoRR Abhishek Sharma, Leo Benac, Sonali Parbhoo, Finale Doshi-Velez
2024	J	`jnl`	Directions of Technical Innovation for Regulatable AI Systems. Commun. ACM Xudong Shen, Hannah Brown, Jiashu Tao, Martin Strobel, Yao Tong, Akshay Narayan, Harold Soh, Finale Doshi-Velez
2024	J	`jnl`	Directly Optimizing Explanations for Desired Properties. CoRR Hiwot Belay Tadesse, Alihan Hüyük, Weiwei Pan, Finale Doshi-Velez
2024	J	`jnl`	Diverse Concept Proposals for Concept Bottleneck Models. CoRR Katrina Brown, Marton Havasi, Finale Doshi-Velez
2024	J	`jnl`	Effective Monitoring of Online Decision-Making Algorithms in Digital Intervention Implementation. CoRR Anna L. Trella, Susobhan Ghosh, Erin E. Bonar, Lara N. Coughlin, Finale Doshi-Velez, Yongyi Guo, Pei-Yao Hung, Inbal Nahum-Shani, Vivek Shetty, Maureen A. Walton, Iris Yan, Kelly W. Zhang, Susan A. Murphy
2024	J	`jnl`	Guarantee Regions for Local Explanations. CoRR Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez
2024	J	`jnl`	Inverse Reinforcement Learning with Multiple Planning Horizons. RLJ Jiayu Yao, Weiwei Pan, Finale Doshi-Velez, Barbara E. Engelhardt
2024	J	`jnl`	Inverse Reinforcement Learning with Multiple Planning Horizons. CoRR Jiayu Yao, Weiwei Pan, Finale Doshi-Velez, Barbara E. Engelhardt
2024	J	`jnl`	Inverse Transition Learning: Learning Dynamics from Demonstrations. CoRR Leo Benac, Abhishek Sharma, Sonali Parbhoo, Finale Doshi-Velez
2024	J	`jnl`	Monitoring Fidelity of Online Reinforcement Learning Algorithms in Clinical Trials. CoRR Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Iris Yan, Finale Doshi-Velez, Susan A. Murphy
2024	J	`jnl`	Non-Stationary Latent Auto-Regressive Bandits. CoRR Anna L. Trella, Walter H. Dempsey, Finale Doshi-Velez, Susan A. Murphy
2024	J	`jnl`	Pruning the Path to Optimal Care: Identifying Systematically Suboptimal Medical Decision-Making with Inverse Reinforcement Learning. CoRR Inko Bovenzi, Adi Carmel, Michael Hu, Rebecca M. Hurwitz, Fiona McBride, Leo Benac, José Roberto Tello-Ayala, Finale Doshi-Velez
2024	A	`conf`	Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. AAMAS Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2024	J	`jnl`	Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. CoRR Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2024	J	`jnl`	Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning. J. Mach. Learn. Res. Sarah Rathnam, Sonali Parbhoo, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2024	J	`jnl`	Semi-parametric Expert Bayesian Network Learning with Gaussian Processes and Horseshoe Priors. CoRR Yidou Weng, Finale Doshi-Velez
2024	J	`jnl`	Shaping AI's Impact on Billions of Lives. CoRR Mariano-Florentino Cuellar, Jeff Dean, Finale Doshi-Velez, John L. Hennessy, Andy Konwinski, Sanmi Koyejo, Pelonomi Moiloa, Emma Pierson, David A. Patterson
2024	J	`jnl`	Task-Relevant Feature Selection with Prediction Focused Mixture Models. Trans. Mach. Learn. Res. Abhishek Sharma, Catherine Zeng, Sanjana Narayanan, Sonali Parbhoo, Roy H. Perlis, Finale Doshi-Velez
2024	—	`conf`	Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. Tiny Papers @ ICLR Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez
2024	J	`jnl`	Towards Integrating Personal Knowledge into Test-Time Predictions. CoRR Isaac Lage, Sonali Parbhoo, Finale Doshi-Velez
2024	J	`jnl`	Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders. CoRR Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
2024	J	`jnl`	Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models. CoRR Ze Yu Zhang, Arun Verma, Finale Doshi-Velez, Bryan Kian Hsiang Low
2024	A*	`conf`	XAI-Lyricist: Improving the Singability of AI-Generated Lyrics with Prosody Explanations. IJCAI Qihao Liang, Xichu Ma, Finale Doshi-Velez, Brian Lim, Ye Wang
2023	J	`jnl`	Adaptive interventions for both accuracy and time in AI-assisted human decision making. CoRR Siddharth Swaroop, Zana Buçinca, Finale Doshi-Velez
2023	J	`jnl`	Bayesian Inverse Transition Learning for Offline Settings. CoRR Leo Benac, Sonali Parbhoo, Finale Doshi-Velez
2023	J	`jnl`	Discovering User Types: Mapping User Traits by Task-Specific Behaviors in Reinforcement Learning. CoRR Lars Lien Ankile, Brian S. Ham, Kevin Mao, Eura Shin, Siddharth Swaroop, Finale Doshi-Velez, Weiwei Pan
2023	J	`jnl`	Learning-to-defer for sequential medical decision-making under uncertainty. Trans. Mach. Learn. Res. Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez
2023	J	`jnl`	Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare. CoRR Shengpu Tang, Maggie Makar, Michael W. Sjoding, Finale Doshi-Velez, Jenna Wiens
2023	J	`jnl`	On the Effective Horizon of Inverse Reinforcement Learning. CoRR Yiqing Xu, Finale Doshi-Velez, David Hsu
2023	J	`jnl`	Online model selection by learning how compositional kernels evolve. Trans. Mach. Learn. Res. Eura Shin, Predrag Klasnja, Susan A. Murphy, Finale Doshi-Velez
2023	A*	`conf`	Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs. ICLR Haotian Fu, Jiayu Yao, Omer Gottesman, Finale Doshi-Velez, George Konidaris
2023	A*	`conf`	Reward Design for an Online Reinforcement Learning Algorithm Supporting Oral Self-Care. AAAI Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
2023	J	`jnl`	Robust Decision-Focused Learning for Reward Transfer. CoRR Abhishek Sharma, Sonali Parbhoo, Omer Gottesman, Finale Doshi-Velez
2023	J	`jnl`	SAP-sLDA: An Interpretable Interface for Exploring Unstructured Text. CoRR Charumathi Badrinath, Weiwei Pan, Finale Doshi-Velez
2023	J	`jnl`	Signature Activation: A Sparse Signal View for Holistic Saliency. CoRR José Roberto Tello-Ayala, Akl C. Fahed, Weiwei Pan, Eugene V. Pomerantsev, Patrick T. Ellinor, Anthony Philippakis, Finale Doshi-Velez
2023	A*	`conf`	The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning. ICML Sarah Rathnam, Sonali Parbhoo, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2023	J	`jnl`	The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning. CoRR Sarah Rathnam, Sonali Parbhoo, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2023	J	`jnl`	Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. CoRR Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez
2023	J	`jnl`	Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities. CoRR Xudong Shen, Hannah Brown, Jiashu Tao, Martin Strobel, Yao Tong, Akshay Narayan, Harold Soh, Finale Doshi-Velez
2023	—	`conf`	Travel-time prediction using neural-network-based mixture models. ANT/EDI40 Abhishek Sharma, Jing Zhang, Daniel Nikovski, Finale Doshi-Velez
2023	J	`jnl`	Why do universal adversarial attacks work on large language models?: Geometry might be the answer. CoRR Varshini Subhash, Anna Bialas, Weiwei Pan, Finale Doshi-Velez
2022	B	`conf`	"If it didn't happen, why would I change my decision?": How Judges Respond to Counterfactual Explanations for the Public Safety Assessment. HCOMP Yaniv Yacoby, Ben Green, Christopher L. Griffin, Finale Doshi-Velez
2022	J	`jnl`	"If it didn't happen, why would I change my decision?": How Judges Respond to Counterfactual Explanations for the Public Safety Assessment. CoRR Yaniv Yacoby, Ben Green, Christopher L. Griffin, Finale Doshi-Velez
2022	J	`jnl`	(When) Are Contrastive Explanations of Reinforcement Learning Helpful? CoRR Sanjana Narayanan, Isaac Lage, Finale Doshi-Velez
2022	J	`jnl`	A Bayesian Approach to Learning Bandit Structure in Markov Decision Processes. CoRR Kelly W. Zhang, Omer Gottesman, Finale Doshi-Velez
2022	—	`conf`	A Joint Learning Approach for Semi-supervised Neural Topic Modeling. SPNLP@ACL Jeffrey Chiu, Rajat Mittal, Neehal Tumma, Abhishek Sharma, Finale Doshi-Velez
2022	J	`jnl`	A Joint Learning Approach for Semi-supervised Neural Topic Modeling. CoRR Jeffrey Chiu, Rajat Mittal, Neehal Tumma, Abhishek Sharma, Finale Doshi-Velez
2022	A*	`conf`	Addressing Leakage in Concept Bottleneck Models. NeurIPS Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez
2022	J	`jnl`	An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks. CoRR Jiayu Yao, Yaniv Yacoby, Beau Coker, Weiwei Pan, Finale Doshi-Velez
2022	J	`jnl`	An interpretable RL framework for pre-deployment modeling in ICU hypotension management. npj Digit. Medicine Kristine Zhang, Henry Wang, Jianzhun Du, Brian Chu, Aldo Arévalo, Ryan Kindle, Leo Anthony Celi, Finale Doshi-Velez
2022	B	`conf`	Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI. HCOMP Q. Vera Liao, Yunfeng Zhang, Ronny Luss, Finale Doshi-Velez, Amit Dhurandhar
2022	J	`jnl`	Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI. CoRR Q. Vera Liao, Yunfeng Zhang, Ronny Luss, Finale Doshi-Velez, Amit Dhurandhar
2022	J	`jnl`	Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines. Algorithms Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
2022	J	`jnl`	Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-implementation Guidelines. CoRR Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
2022	J	`jnl`	Does the explanation satisfy your needs?: A unified view of properties of explanations. CoRR Zixi Chen, Varshini Subhash, Marton Havasi, Weiwei Pan, Finale Doshi-Velez
2022	J	`jnl`	Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. CoRR 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 A. Sloman, Shannon Vallor, Toby Walsh
2022	J	`jnl`	Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making. CoRR Sonali Parbhoo, Shalmali Joshi, Finale Doshi-Velez
2022	—	`conf`	Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation. CHIL Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill
2022	—	`conf`	Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models. MLHC Carissa Wu, Sonali Parbhoo, Marton Havasi, Finale Doshi-Velez
2022	A*	`conf`	Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare. NeurIPS Shengpu Tang, Maggie Makar, Michael W. Sjoding, Finale Doshi-Velez, Jenna Wiens
2022	J	`jnl`	Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables. J. Mach. Learn. Res. Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
2022	J	`jnl`	Modeling Mobile Health Users as Reinforcement Learning Agents. CoRR Eura Shin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2022	J	`jnl`	Policy Optimization with Sparse Global Contrastive Explanations. CoRR Jiayu Yao, Sonali Parbhoo, Weiwei Pan, Finale Doshi-Velez
2022	J	`jnl`	Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care. CoRR Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy
2022	J	`jnl`	Success of Uncertainty-Aware Deep Models Depends on Data Manifold Geometry. CoRR Mark Penrod, Harrison Termotto, Varshini Reddy, Jiayu Yao, Finale Doshi-Velez, Weiwei Pan
2022	C	`conf`	Towards Robust Off-Policy Evaluation via Human Inputs. AIES Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
2022	J	`jnl`	Towards Robust Off-Policy Evaluation via Human Inputs. CoRR Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
2022	A	`conf`	Wide Mean-Field Bayesian Neural Networks Ignore the Data. AISTATS Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez
2022	J	`jnl`	Wide Mean-Field Bayesian Neural Networks Ignore the Data. CoRR Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez
2021	A*	`conf`	Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement. ICML Andrew Slavin Ross, Finale Doshi-Velez
2021	J	`jnl`	Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement. CoRR Andrew Slavin Ross, Finale Doshi-Velez
2021	J	`jnl`	Comparison and Unification of Three Regularization Methods in Batch Reinforcement Learning. CoRR Sarah Rathnam, Susan A. Murphy, Finale Doshi-Velez
2021	J	`jnl`	Depth-Bounded Statistical PCFG Induction as a Model of Human Grammar Acquisition. Comput. Linguistics Lifeng Jin, Lane Schwartz, Finale Doshi-Velez, Timothy Miller, William Schuler
2021	A*	`conf`	Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens. CHI Maia L. Jacobs, Jeffrey He, Melanie F. Pradier, Barbara D. Lam, Andrew C. Ahn, Thomas H. McCoy, Roy H. Perlis, Finale Doshi-Velez, Krzysztof Z. Gajos
2021	J	`jnl`	Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens. CoRR Maia L. Jacobs, Jeffrey He, Melanie F. Pradier, Barbara D. Lam, Andrew C. Ahn, Thomas H. McCoy, Roy H. Perlis, Finale Doshi-Velez, Krzysztof Z. Gajos
2021	A*	`conf`	Evaluating the Interpretability of Generative Models by Interactive Reconstruction. CHI Andrew Slavin Ross, Nina Chen, Elisa Zhao Hang, Elena L. Glassman, Finale Doshi-Velez
2021	J	`jnl`	Evaluating the Interpretability of Generative Models by Interactive Reconstruction. CoRR Andrew Slavin Ross, Nina Chen, Elisa Zhao Hang, Elena L. Glassman, Finale Doshi-Velez
2021	J	`jnl`	Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation. CoRR Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill
2021	J	`jnl`	Identifying Decision Points for Safe and Interpretable Reinforcement Learning in Hypotension Treatment. CoRR Kristine Zhang, Yuanheng Wang, Jianzhun Du, Brian Chu, Leo Anthony Celi, Ryan Kindle, Finale Doshi-Velez
2021	—	`conf`	Interactive Cohort Analysis and Hypothesis Discovery by Exploring Temporal Patterns in Population-Level Health Records. VAHC Tianyi Zhang, Thomas H. McCoy, Roy H. Perlis, Finale Doshi-Velez, Elena L. Glassman
2021	A*	`conf`	Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning. NeurIPS Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe
2021	J	`jnl`	Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning. CoRR Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe
2021	Misc	`conf`	Learning Predictive and Interpretable Timeseries Summaries from ICU Data. AMIA Nari Johnson, Sonali Parbhoo, Andrew Slavin Ross, Finale Doshi-Velez
2021	J	`jnl`	Learning Predictive and Interpretable Timeseries Summaries from ICU Data. CoRR Nari Johnson, Sonali Parbhoo, Andrew Slavin Ross, Finale Doshi-Velez
2021	J	`jnl`	Learning Under Adversarial and Interventional Shifts. CoRR Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
2021	J	`jnl`	Machine Learning Techniques for Accountability. AI Mag. Been Kim, Finale Doshi-Velez
2021	J	`jnl`	On Learning Prediction-Focused Mixtures. CoRR Abhishek Sharma, Catherine Zeng, Sanjana Narayanan, Sonali Parbhoo, Finale Doshi-Velez
2021	J	`jnl`	Online structural kernel selection for mobile health. CoRR Eura Shin, Pedja Klasnja, Susan A. Murphy, Finale Doshi-Velez
2021	J	`jnl`	Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. J. Artif. Intell. Res. Mike Wu, Sonali Parbhoo, Michael C. Hughes, Volker Roth, Finale Doshi-Velez
2021	—	`conf`	Power Constrained Bandits. MLHC Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2021	J	`jnl`	Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty. CoRR Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez
2021	J	`jnl`	Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible. CoRR Melanie F. Pradier, Javier Zazo, Sonali Parbhoo, Roy H. Perlis, Maurizio Zazzi, Finale Doshi-Velez
2021	J	`jnl`	Promises and Pitfalls of Black-Box Concept Learning Models. CoRR Anita Mahinpei, Justin Clark, Isaac Lage, Finale Doshi-Velez, Weiwei Pan
2021	A*	`conf`	State Relevance for Off-Policy Evaluation. ICML Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez
2021	J	`jnl`	State Relevance for Off-Policy Evaluation. CoRR Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez
2021	J	`jnl`	Wide Mean-Field Variational Bayesian Neural Networks Ignore the Data. CoRR Beau Coker, Weiwei Pan, Finale Doshi-Velez
2020	C	`conf`	Active Screening on Recurrent Diseases Contact Networks with Uncertainty: A Reinforcement Learning Approach. MABS Han-Ching Ou, Kai Wang, Finale Doshi-Velez, Milind Tambe
2020	J	`jnl`	Artificial Intelligence & Cooperation. CoRR Elisa Bertino, Finale Doshi-Velez, Maria L. Gini, Daniel Lopresti, David C. Parkes
2020	J	`jnl`	BaCOUn: Bayesian Classifers with Out-of-Distribution Uncertainty. CoRR Théo Guénais, Dimitris Vamvourellis, Yaniv Yacoby, Finale Doshi-Velez, Weiwei Pan
2020	J	`jnl`	Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders. CoRR Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
2020	—	`conf`	Defining admissible rewards for high-confidence policy evaluation in batch reinforcement learning. CHIL Niranjani Prasad, Barbara E. Engelhardt, Finale Doshi-Velez
2020	A*	`conf`	Ensembles of Locally Independent Prediction Models. AAAI Andrew Slavin Ross, Weiwei Pan, Leo A. Celi, Finale Doshi-Velez
2020	J	`jnl`	Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks. CoRR Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
2020	J	`jnl`	Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning. CoRR Joseph Futoma, Muhammad A. Masood, Finale Doshi-Velez
2020	A*	`conf`	Incorporating Interpretable Output Constraints in Bayesian Neural Networks. NeurIPS Wanqian Yang, Lars Lorch, Moritz A. Graule, Himabindu Lakkaraju, Finale Doshi-Velez
2020	J	`jnl`	Incorporating Interpretable Output Constraints in Bayesian Neural Networks. CoRR Wanqian Yang, Lars Lorch, Moritz A. Graule, Himabindu Lakkaraju, Finale Doshi-Velez
2020	A*	`conf`	Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. ICML Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo A. Celi, Emma Brunskill, Finale Doshi-Velez
2020	J	`jnl`	Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. CoRR Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Anthony Celi, Emma Brunskill, Finale Doshi-Velez
2020	Misc	`conf`	Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients. AMIA Mingyu Lu, Zachary Shahn, Daby Sow, Finale Doshi-Velez, Li-Wei H. Lehman
2020	J	`jnl`	Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Sepsis Treatment. CoRR Mingyu Lu, Zachary Shahn, Daby Sow, Finale Doshi-Velez, Li-Wei H. Lehman
2020	J	`jnl`	Learned Uncertainty-Aware (LUNA) Bases for Bayesian Regression using Multi-Headed Auxiliary Networks. CoRR Sujay Thakur, Cooper Lorsung, Yaniv Yacoby, Finale Doshi-Velez, Weiwei Pan
2020	J	`jnl`	Learning Interpretable Concept-Based Models with Human Feedback. CoRR Isaac Lage, Finale Doshi-Velez
2020	A*	`conf`	Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs. NeurIPS Jianzhun Du, Joseph Futoma, Finale Doshi-Velez
2020	J	`jnl`	Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs. CoRR Jianzhun Du, Joseph Futoma, Finale Doshi-Velez
2020	J	`jnl`	PAC Bounds for Imitation and Model-based Batch Learning of Contextual Markov Decision Processes. CoRR Yash Nair, Finale Doshi-Velez
2020	J	`jnl`	POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning. CoRR Joseph Futoma, Michael C. Hughes, Finale Doshi-Velez
2020	A	`conf`	POPCORN: Partially Observed Prediction Constrained Reinforcement Learning. AISTATS Joseph Futoma, Michael C. Hughes, Finale Doshi-Velez
2020	A	`conf`	PoRB-Nets: Poisson Process Radial Basis Function Networks. UAI Beau Coker, Melanie Fernandes Pradier, Finale Doshi-Velez
2020	J	`jnl`	Power-Constrained Bandits. CoRR Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2020	A	`conf`	Prediction Focused Topic Models via Feature Selection. AISTATS Jason Ren, Russell Kunes, Finale Doshi-Velez
2020	—	`ed.`	Proceedings of the Machine Learning for Healthcare Conference, MLHC 2020, 7-8 August 2020, Virtual Event, Durham, NC, USA. MLHC Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens
2020	A*	`conf`	Regional Tree Regularization for Interpretability in Deep Neural Networks. AAAI Mike Wu, Sonali Parbhoo, Michael C. Hughes, Ryan Kindle, Leo A. Celi, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
2020	—	`conf`	Transfer Learning from Well-Curated to Less-Resourced Populations with HIV. MLHC Sonali Parbhoo, Mario Wieser, Volker Roth, Finale Doshi-Velez
2019	J	`jnl`	A Particle-Based Variational Approach to Bayesian Non-negative Matrix Factorization. J. Mach. Learn. Res. Muhammad A. Masood, Finale Doshi-Velez
2019	J	`jnl`	A general method for regularizing tensor decomposition methods via pseudo-data. CoRR Omer Gottesman, Weiwei Pan, Finale Doshi-Velez
2019	J	`jnl`	An Evaluation of the Human-Interpretability of Explanation. CoRR Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Sam Gershman, Finale Doshi-Velez
2019	J	`jnl`	Assessing topic model relevance: Evaluation and informative priors. Stat. Anal. Data Min. Angela Fan, Finale Doshi-Velez, Luke Miratrix
2019	—	`conf`	Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders. AABI Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
2019	J	`jnl`	Combining Parametric and Nonparametric Models for Off-Policy Evaluation. CoRR Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez
2019	A*	`conf`	Combining parametric and nonparametric models for off-policy evaluation. ICML Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez
2019	J	`jnl`	Defining Admissible Rewards for High Confidence Policy Evaluation. CoRR Niranjani Prasad, Barbara E. Engelhardt, Finale Doshi-Velez
2019	A*	`conf`	Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies. IJCAI Muhammad A. Masood, Finale Doshi-Velez
2019	J	`jnl`	Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies. CoRR Muhammad A. Masood, Finale Doshi-Velez
2019	J	`jnl`	Ensembles of Locally Independent Prediction Models. CoRR Andrew Slavin Ross, Weiwei Pan, Leo Anthony Celi, Finale Doshi-Velez
2019	A*	`conf`	Exploring Computational User Models for Agent Policy Summarization. IJCAI Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, Ofra Amir
2019	J	`jnl`	Exploring Computational User Models for Agent Policy Summarization. CoRR Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, Ofra Amir
2019	B	`conf`	Human Evaluation of Models Built for Interpretability. HCOMP Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Samuel J. Gershman, Finale Doshi-Velez
2019	J	`jnl`	Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning. CoRR Xuefeng Peng, Yi Ding, David Wihl, Omer Gottesman, Matthieu Komorowski, Li-Wei H. Lehman, Andrew Slavin Ross, Aldo Faisal, Finale Doshi-Velez
2019	J	`jnl`	Learning Deep Bayesian Latent Variable Regression Models that Generalize: When Non-identifiability is a Problem. CoRR Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
2019	J	`jnl`	Model Selection in Bayesian Neural Networks via Horseshoe Priors. J. Mach. Learn. Res. Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
2019	J	`jnl`	Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. CoRR Mike Wu, Sonali Parbhoo, Michael C. Hughes, Volker Roth, Finale Doshi-Velez
2019	J	`jnl`	Output-Constrained Bayesian Neural Networks. CoRR Wanqian Yang, Lars Lorch, Moritz A. Graule, Srivatsan Srinivasan, Anirudh Suresh, Jiayu Yao, Melanie F. Pradier, Finale Doshi-Velez
2019	J	`jnl`	Prediction Focused Topic Models for Electronic Health Records. CoRR Jason Ren, Russell Kunes, Finale Doshi-Velez
2019	J	`jnl`	Prediction Focused Topic Models via Vocab Selection. CoRR Jason Ren, Russell Kunes, Finale Doshi-Velez
2019	—	`ed.`	Proceedings of the Machine Learning for Healthcare Conference, MLHC 2019, 9-10 August 2019, Ann Arbor, Michigan, USA. MLHC Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens
2019	J	`jnl`	Quality of Uncertainty Quantification for Bayesian Neural Network Inference. CoRR Jiayu Yao, Weiwei Pan, Soumya Ghosh, Finale Doshi-Velez
2019	J	`jnl`	Regional Tree Regularization for Interpretability in Black Box Models. CoRR Mike Wu, Sonali Parbhoo, Michael C. Hughes, Ryan Kindle, Leo A. Celi, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
2019	J	`jnl`	Summarizing agent strategies. Auton. Agents Multi Agent Syst. Ofra Amir, Finale Doshi-Velez, David Sarne
2019	A	`conf`	Toward Robust Policy Summarization. AAMAS Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, Ofra Amir
2019	J	`jnl`	Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks. CoRR Beau Coker, Melanie F. Pradier, Finale Doshi-Velez
2019	A*	`conf`	Truly Batch Apprenticeship Learning with Deep Successor Features. IJCAI Donghun Lee, Srivatsan Srinivasan, Finale Doshi-Velez
2019	J	`jnl`	Truly Batch Apprenticeship Learning with Deep Successor Features. CoRR Donghun Lee, Srivatsan Srinivasan, Finale Doshi-Velez
2019	—	`conf`	Unsupervised Learning of PCFGs with Normalizing Flow. ACL (1) Lifeng Jin, Finale Doshi-Velez, Timothy Miller, Lane Schwartz, William Schuler
2018	A	`conf`	Agent Strategy Summarization. AAMAS Ofra Amir, Finale Doshi-Velez, David Sarne
2018	J	`jnl`	Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters. CoRR Aniruddh Raghu, Omer Gottesman, Yao Liu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill
2018	A*	`conf`	Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. AAAI Mike Wu, Michael C. Hughes, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
2018	A*	`conf`	Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning. ICML Stefan Depeweg, José Miguel Hernández-Lobato, Finale Doshi-Velez, Steffen Udluft
2018	A*	`conf`	Depth-bounding is effective: Improvements and Evaluation of Unsupervised PCFG Induction. EMNLP Lifeng Jin, Finale Doshi-Velez, Timothy Miller, William Schuler, Lane Schwartz
2018	J	`jnl`	Depth-bounding is effective: Improvements and evaluation of unsupervised PCFG induction. CoRR Lifeng Jin, Finale Doshi-Velez, Timothy Miller, William Schuler, Lane Schwartz
2018	J	`jnl`	Evaluating Reinforcement Learning Algorithms in Observational Health Settings. CoRR Omer Gottesman, Fredrik D. Johansson, Joshua Meier, Jack Dent, Donghun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, Jiayu Yao, Isaac Lage, Christopher Mosch, Li-Wei H. Lehman, Matthieu Komorowski, Aldo Faisal, Leo Anthony Celi, David A. Sontag, Finale Doshi-Velez
2018	J	`jnl`	How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation. CoRR Menaka Narayanan, Emily Chen, Jeffrey He, Been Kim, Sam Gershman, Finale Doshi-Velez
2018	A*	`conf`	Human-in-the-Loop Interpretability Prior. NeurIPS Isaac Lage, Andrew Slavin Ross, Samuel J. Gershman, Been Kim, Finale Doshi-Velez
2018	J	`jnl`	Human-in-the-Loop Interpretability Prior. CoRR Isaac Lage, Andrew Slavin Ross, Been Kim, Samuel J. Gershman, Finale Doshi-Velez
2018	Misc	`conf`	Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning. AMIA Xuefeng Peng, Yi Ding, David Wihl, Omer Gottesman, Matthieu Komorowski, Li-Wei H. Lehman, Andrew Slavin Ross, Aldo Faisal, Finale Doshi-Velez
2018	A*	`conf`	Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients. AAAI Andrew Slavin Ross, Finale Doshi-Velez
2018	J	`jnl`	Latent Projection BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights. CoRR Melanie F. Pradier, Weiwei Pan, Jiayu Yao, Soumya Ghosh, Finale Doshi-Velez
2018	J	`jnl`	Learning Qualitatively Diverse and Interpretable Rules for Classification. CoRR Andrew Slavin Ross, Weiwei Pan, Finale Doshi-Velez
2018	J	`jnl`	PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models. IEEE Trans. Vis. Comput. Graph. Michael Glueck, Mahdi Pakdaman Naeini, Finale Doshi-Velez, Fanny Chevalier, Azam Khan, Daniel Wigdor, Michael Brudno
2018	—	`ed.`	Proceedings of the Machine Learning for Healthcare Conference, MLHC 2018, 17-18 August 2018, Palo Alto, California MLHC Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens
2018	J	`jnl`	Representation Balancing MDPs for Off-Policy Policy Evaluation. CoRR Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill
2018	A*	`conf`	Representation Balancing MDPs for Off-policy Policy Evaluation. NeurIPS Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo A. Faisal, Finale Doshi-Velez, Emma Brunskill
2018	A	`conf`	Semi-Supervised Prediction-Constrained Topic Models. AISTATS Michael C. Hughes, Gabriel Hope, Leah Weiner, Thomas H. McCoy Jr., Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez
2018	A*	`conf`	Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors. ICML Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
2018	J	`jnl`	Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors. CoRR Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
2018	J	`jnl`	Unsupervised Grammar Induction with Depth-bounded PCFG. CoRR Lifeng Jin, Finale Doshi-Velez, Timothy Miller, William Schuler, Lane Schwartz
2018	J	`jnl`	Unsupervised Grammar Induction with Depth-bounded PCFG. Trans. Assoc. Comput. Linguistics Lifeng Jin, Finale Doshi-Velez, Timothy Miller, William Schuler, Lane Schwartz
2018	A	`conf`	Weighted Tensor Decomposition for Learning Latent Variables with Partial Data. AISTATS Omer Gottesman, Weiwei Pan, Finale Doshi-Velez
2017	J	`jnl`	A Bayesian Framework for Learning Rule Sets for Interpretable Classification. J. Mach. Learn. Res. Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille
2017	J	`jnl`	A Roadmap for a Rigorous Science of Interpretability. CoRR Finale Doshi-Velez, Been Kim
2017	J	`jnl`	Accountability of AI Under the Law: The Role of Explanation. CoRR Finale Doshi-Velez, Mason Kortz, Ryan Budish, Chris Bavitz, Sam Gershman, David O'Brien, Stuart Schieber, James Waldo, David Weinberger, Alexandra Wood
2017	J	`jnl`	Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. CoRR Mike Wu, Michael C. Hughes, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
2017	—	`conf`	Combining Kernel and Model Based Learning for HIV Therapy Selection. CRI Sonali Parbhoo, Jasmina Bogojeska, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
2017	J	`jnl`	Decomposition of Uncertainty for Active Learning and Reliable Reinforcement Learning in Stochastic Systems. CoRR Stefan Depeweg, José Miguel Hernández-Lobato, Finale Doshi-Velez, Steffen Udluft
2017	J	`jnl`	Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients. CoRR Andrew Slavin Ross, Finale Doshi-Velez
2017	—	`conf`	Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks. ICLR (Poster) Stefan Depeweg, José Miguel Hernández-Lobato, Finale Doshi-Velez, Steffen Udluft
2017	—	`conf`	Predicting intervention onset in the ICU with switching state space models. CRI Marzyeh Ghassemi, Mike Wu, Michael C. Hughes, Peter Szolovits, Finale Doshi-Velez
2017	J	`jnl`	Prediction-Constrained Topic Models for Antidepressant Recommendation. CoRR Michael C. Hughes, Gabriel Hope, Leah Weiner, Thomas H. McCoy Jr., Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez
2017	J	`jnl`	Prediction-Constrained Training for Semi-Supervised Mixture and Topic Models. CoRR Michael C. Hughes, Leah Weiner, Gabriel Hope, Thomas H. McCoy Jr., Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez
2017	—	`ed.`	Proceedings of the Machine Learning for Healthcare Conference, MLHC 2017, Boston, Massachusetts, USA, 18-19 August 2017 MLHC Finale Doshi-Velez, Jim Fackler, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens
2017	J	`jnl`	Promoting Domain-Specific Terms in Topic Models with Informative Priors. CoRR Angela Fan, Finale Doshi-Velez, Luke Miratrix
2017	J	`jnl`	Restricted Indian buffet processes. Stat. Comput. Finale Doshi-Velez, Sinead A. Williamson
2017	A*	`conf`	Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations. IJCAI Andrew Slavin Ross, Michael C. Hughes, Finale Doshi-Velez
2017	J	`jnl`	Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations. CoRR Andrew Slavin Ross, Michael C. Hughes, Finale Doshi-Velez
2017	A*	`conf`	Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes. AAAI Taylor W. Killian, George Dimitri Konidaris, Finale Doshi-Velez
2017	—	`conf`	Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes. NIPS Taylor W. Killian, Samuel Daulton, Finale Doshi-Velez, George Dimitri Konidaris
2017	J	`jnl`	Robust and Efficient Transfer Learning with Hidden-Parameter Markov Decision Processes. CoRR Taylor W. Killian, Samuel Daulton, George Dimitri Konidaris, Finale Doshi-Velez
2017	J	`jnl`	Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database. J. Am. Medical Informatics Assoc. Mike Wu, Marzyeh Ghassemi, Mengling Feng, Leo A. Celi, Peter Szolovits, Finale Doshi-Velez
2016	J	`jnl`	A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations. CoRR Weiwei Pan, Finale Doshi-Velez
2016	J	`jnl`	An Empirical Comparison of Sampling Quality Metrics: A Case Study for Bayesian Nonnegative Matrix Factorization. CoRR Arjumand Masood, Weiwei Pan, Finale Doshi-Velez
2016	A*	`conf`	Bayesian Rule Sets for Interpretable Classification. ICDM Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille
2016	A	`conf`	Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice. SDM Xide Xia, Pavlos Protopapas, Finale Doshi-Velez
2016	J	`jnl`	Cross-Corpora Unsupervised Learning of Trajectories in Autism Spectrum Disorders. J. Mach. Learn. Res. Huseyin Melih Elibol, Vincent Nguyen, Scott W. Linderman, Matthew J. Johnson, Amna Hashmi, Finale Doshi-Velez
2016	A*	`conf`	Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations. IJCAI Finale Doshi-Velez, George Dimitri Konidaris
2016	J	`jnl`	Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models. CoRR Viktoriya Krakovna, Finale Doshi-Velez
2016	J	`jnl`	Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models. CoRR Viktoriya Krakovna, Finale Doshi-Velez
2016	J	`jnl`	Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks. CoRR Stefan Depeweg, José Miguel Hernández-Lobato, Finale Doshi-Velez, Steffen Udluft
2016	B	`conf`	Memory-Bounded Left-Corner Unsupervised Grammar Induction on Child-Directed Input. COLING Cory Shain, William Bryce, Lifeng Jin, Victoria Krakovna, Finale Doshi-Velez, Timothy Miller, William Schuler, Lane Schwartz
2016	—	`ed.`	Proceedings of the 1st Machine Learning for Healthcare, MLHC 2016, Los Angeles, CA, USA, August 19-20, 2016 MLHC Finale Doshi-Velez, Jim Fackler, David C. Kale, Byron C. Wallace, Jenna Wiens
2016	A	`conf`	Spectral M-estimation with Applications to Hidden Markov Models. AISTATS Dustin Tran, Minjae Kim, Finale Doshi-Velez
2016	J	`jnl`	Spectral M-estimation with Applications to Hidden Markov Models. CoRR Dustin Tran, Minjae Kim, Finale Doshi-Velez
2016	J	`jnl`	Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes. CoRR Taylor W. Killian, George Dimitri Konidaris, Finale Doshi-Velez
2015	J	`jnl`	Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. Finale Doshi-Velez, David Pfau, Frank D. Wood, Nicholas Roy
2015	A*	`conf`	Graph-Sparse LDA: A Topic Model with Structured Sparsity. AAAI Finale Doshi-Velez, Byron C. Wallace, Ryan P. Adams
2015	—	`conf`	Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction. NIPS Been Kim, Julie A. Shah, Finale Doshi-Velez
2015	J	`jnl`	Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems. CoRR Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille
2014	J	`jnl`	Graph-Sparse LDA: A Topic Model with Structured Sparsity. CoRR Finale Doshi-Velez, Byron C. Wallace, Ryan P. Adams
2014	—	`conf`	Hidden Parameter Markov Decision Processes: An Emerging Paradigm for Modeling Families of Related Tasks. AAAI Fall Symposia George Dimitri Konidaris, Finale Doshi-Velez
2014	—	`ed.`	Modern Artificial Intelligence for Health Analytics, Papers from the 2014 AAAI Workshop, Québec City, Québec, Canada, July 27, 2014 AAAI Workshop: Modern Artificial Intelligence for Health Analytics Finale Doshi-Velez, David C. Kale, Byron C. Wallace, Jenna Wiens
2014	—	`conf`	Preface. AAAI Workshop: Modern Artificial Intelligence for Health Analytics Finale Doshi-Velez, David C. Kale, Byron C. Wallace, Jenna Wiens
2014	A*	`conf`	Unfolding physiological state: mortality modelling in intensive care units. KDD Marzyeh Ghassemi, Tristan Naumann, Finale Doshi-Velez, Nicole Brimmer, Rohit Joshi, Anna Rumshisky, Peter Szolovits
2013	J	`jnl`	Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations. CoRR Finale Doshi-Velez, George Dimitri Konidaris
2012	A*	`conf`	A Bayesian nonparametric approach to modeling battery health. ICRA Joshua Mason Joseph, Finale Doshi-Velez, Nicholas Roy
2012	—	`—`	Bayesian nonparametric methods for reinforcement learning in partially observable domains. Finale Doshi-Velez
2012	J	`jnl`	Correlated Non-Parametric Latent Feature Models CoRR Finale Doshi-Velez, Zoubin Ghahramani
2012	J	`jnl`	Reinforcement learning with limited reinforcement: Using Bayes risk for active learning in POMDPs. Artif. Intell. Finale Doshi-Velez, Joelle Pineau, Nicholas Roy
2011	J	`jnl`	A Bayesian nonparametric approach to modeling motion patterns. Auton. Robots Joshua Mason Joseph, Finale Doshi-Velez, Albert S. Huang, Nicholas Roy
2011	B	`conf`	A Comparison of Human and Agent Reinforcement Learning in Partially Observable Domains. CogSci Finale Doshi-Velez, Zoubin Ghahramani
2011	—	`conf`	Organizing Committee. AAAI Spring Symposium: Computational Physiology Mark Buller, Paul Cuddihy, Finale Doshi-Velez
2011	J	`jnl`	Reports of the AAAI 2011 Spring Symposia. AI Mag. Mark Buller, Paul Cuddihy, Ernest Davis, Patrick Doherty, Finale Doshi-Velez, Esra Erdem, Douglas H. Fisher, Nancy L. Green, Knut Hinkelmann, Mary Lou Maher, James McLurkin, Rajiv T. Maheswaran, Sara Rubinelli, Nathan Schurr, Donia Scott, Dylan A. Shell, Pedro A. Szekely, Barbara Thönssen, Arnold B. Urken
2010	A*	`conf`	A Bayesian Nonparametric Approach to Modeling Mobility Patterns. AAAI Joshua Mason Joseph, Finale Doshi-Velez, Nicholas Roy
2010	A*	`conf`	Nonparametric Bayesian Approaches for Reinforcement Learning in Partially Observable Domains. AAAI Finale Doshi-Velez
2010	—	`conf`	Nonparametric Bayesian Policy Priors for Reinforcement Learning. NIPS Finale Doshi-Velez, David Wingate, Nicholas Roy, Joshua B. Tenenbaum
2009	A*	`conf`	Accelerated sampling for the Indian Buffet Process. ICML Finale Doshi-Velez, Zoubin Ghahramani
2009	A	`conf`	Correlated Non-Parametric Latent Feature Models. UAI Finale Doshi-Velez, Zoubin Ghahramani
2009	—	`conf`	Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process. NIPS Finale Doshi-Velez, David A. Knowles, Shakir Mohamed, Zoubin Ghahramani
2009	—	`conf`	The Infinite Partially Observable Markov Decision Process. NIPS Finale Doshi-Velez