default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDFinale Doshi-Velez
Finale Doshi
Person information
- affiliation: Harvard University, USA
- affiliation (former): MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j27]Jiayu Yao, Weiwei Pan, Finale Doshi-Velez, Barbara E. Engelhardt:
Inverse Reinforcement Learning with Multiple Planning Horizons. RLJ 3: 1138-1167 (2024)- [j26]Xudong Shen, Hannah Brown, Jiashu Tao
, Martin Strobel, Yao Tong, Akshay Narayan, Harold Soh, Finale Doshi-Velez:
Directions of Technical Innovation for Regulatable AI Systems. Commun. ACM 67(11): 82-89 (2024) - [j25]Sarah Rathnam, Sonali Parbhoo, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning. J. Mach. Learn. Res. 25: 255:1-255:48 (2024) - [j24]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) - [c91]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: 1482-1491 - [c90]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 - [c89]Qihao Liang, Xichu Ma, Finale Doshi-Velez, Brian Lim, Ye Wang:
XAI-Lyricist: Improving the Singability of AI-Generated Lyrics with Prosody Explanations. IJCAI 2024: 7877-7885 - [c88]Siddharth Swaroop, Zana Buçinca, Krzysztof Z. Gajos, Finale Doshi-Velez:
Accuracy-Time Tradeoffs in AI-Assisted Decision Making under Time Pressure. IUI 2024: 138-154 - [i122]Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. CoRR abs/2401.14923 (2024) - [i121]Yidou Weng, Finale Doshi-Velez:
Semi-parametric Expert Bayesian Network Learning with Gaussian Processes and Horseshoe Priors. CoRR abs/2401.16419 (2024) - [i120]Anna L. Trella, Walter Dempsey, Finale Doshi-Velez, Susan A. Murphy:
Non-Stationary Latent Auto-Regressive Bandits. CoRR abs/2402.03110 (2024) - [i119]Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez:
Guarantee Regions for Local Explanations. CoRR abs/2402.12737 (2024) - [i118]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 abs/2402.17003 (2024) - [i117]Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez:
Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders. CoRR abs/2403.08941 (2024) - [i116]Tom Zick, Mason Kortz, David Eaves, Finale Doshi-Velez:
AI Procurement Checklists: Revisiting Implementation in the Age of AI Governance. CoRR abs/2404.14660 (2024) - [i115]Eura Nofshin, Esther Brown, Brian Lim, Weiwei Pan, Finale Doshi-Velez:
A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning. CoRR abs/2406.00116 (2024) - [i114]Isaac Lage, Sonali Parbhoo, Finale Doshi-Velez:
Towards Integrating Personal Knowledge into Test-Time Predictions. CoRR abs/2406.08636 (2024) - [i113]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 abs/2407.14845 (2024) - [i112]Anna L. Trella, Kelly W. Zhang, Hinal Jajal, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy:
A Deployed Online Reinforcement Learning Algorithm In An Oral Health Clinical Trial. CoRR abs/2409.02069 (2024) - [i111]Anna L. Trella, Susobhan Ghosh, Erin 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:
Effective Monitoring of Online Decision-Making Algorithms in Digital Intervention Implementation. CoRR abs/2409.10526 (2024) - [i110]Jiayu Yao, Weiwei Pan, Finale Doshi-Velez, Barbara E. Engelhardt:
Inverse Reinforcement Learning with Multiple Planning Horizons. CoRR abs/2409.18051 (2024) - [i109]Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch, Finale Doshi-Velez, Krzysztof Z. Gajos:
Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills. CoRR abs/2410.04253 (2024) - [i108]Abhishek Sharma, Leo Benac, Sonali Parbhoo, Finale Doshi-Velez:
Decision-Point Guided Safe Policy Improvement. CoRR abs/2410.09361 (2024) - [i107]Hiwot Belay Tadesse, Alihan Hüyük, Weiwei Pan, Finale Doshi-Velez:
Directly Optimizing Explanations for Desired Properties. CoRR abs/2410.23880 (2024) - 2023
- [j23]Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez:
Learning-to-defer for sequential medical decision-making under uncertainty. Trans. Mach. Learn. Res. 2023 (2023) - [j22]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) - [c87]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: 15724-15730 - [c86]Abhishek Sharma, Jing Zhang, Daniel Nikovski, Finale Doshi-Velez:
Travel-time prediction using neural-network-based mixture models. ANT/EDI40 2023: 1033-1038 - [c85]Haotian Fu, Jiayu Yao, Omer Gottesman, Finale Doshi-Velez, George Konidaris:
Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs. ICLR 2023 - [c84]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: 28746-28767 - [i106]Abhishek Sharma, Sonali Parbhoo, Omer Gottesman, Finale Doshi-Velez:
Robust Decision-Focused Learning for Reward Transfer. CoRR abs/2304.03365 (2023) - [i105]Shengpu Tang, Maggie Makar, Michael W. Sjoding, Finale Doshi-Velez, Jenna Wiens:
Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare. CoRR abs/2305.01738 (2023) - [i104]Siddharth Swaroop, Zana Buçinca, Finale Doshi-Velez:
Adaptive interventions for both accuracy and time in AI-assisted human decision making. CoRR abs/2306.07458 (2023) - [i103]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 abs/2306.11208 (2023) - [i102]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 abs/2306.12609 (2023) - [i101]Yiqing Xu, Finale Doshi-Velez, David Hsu:
On the Effective Horizon of Inverse Reinforcement Learning. CoRR abs/2307.06541 (2023) - [i100]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 abs/2307.08169 (2023) - [i99]Charumathi Badrinath, Weiwei Pan, Finale Doshi-Velez:
SAP-sLDA: An Interpretable Interface for Exploring Unstructured Text. CoRR abs/2308.01420 (2023) - [i98]Leo Benac, Sonali Parbhoo, Finale Doshi-Velez:
Bayesian Inverse Transition Learning for Offline Settings. CoRR abs/2308.05075 (2023) - [i97]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 abs/2309.00254 (2023) - [i96]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 abs/2309.11443 (2023) - [i95]Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez:
Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. CoRR abs/2312.09983 (2023) - 2022
- [j21]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): 255 (2022) - [j20]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: 244:1-244:54 (2022) - [j19]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) - [c83]Jeffrey Chiu, Rajat Mittal, Neehal Tumma, Abhishek Sharma, Finale Doshi-Velez:
A Joint Learning Approach for Semi-supervised Neural Topic Modeling. SPNLP@ACL 2022: 40-51 - [c82]Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju:
Towards Robust Off-Policy Evaluation via Human Inputs. AIES 2022: 686-699 - [c81]Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez:
Wide Mean-Field Bayesian Neural Networks Ignore the Data. AISTATS 2022: 5276-5333 - [c80]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: 397-410 - [c79]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: 147-159 - [c78]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: 219-230 - [c77]Carissa Wu, Sonali Parbhoo, Marton Havasi, Finale Doshi-Velez:
Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models. MLHC 2022: 648-672 - [c76]Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez:
Addressing Leakage in Concept Bottleneck Models. NeurIPS 2022 - [c75]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 - [i94]Sonali Parbhoo, Shalmali Joshi, Finale Doshi-Velez:
Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making. CoRR abs/2201.08262 (2022) - [i93]Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez:
Wide Mean-Field Bayesian Neural Networks Ignore the Data. CoRR abs/2202.11670 (2022) - [i92]Jeffrey Chiu, Rajat Mittal, Neehal Tumma, Abhishek Sharma, Finale Doshi-Velez:
A Joint Learning Approach for Semi-supervised Neural Topic Modeling. CoRR abs/2204.03208 (2022) - [i91]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 abs/2205.05424 (2022) - [i90]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 abs/2206.03944 (2022) - [i89]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 abs/2206.10847 (2022) - [i88]Jiayu Yao, Sonali Parbhoo, Weiwei Pan, Finale Doshi-Velez:
Policy Optimization with Sparse Global Contrastive Explanations. CoRR abs/2207.06269 (2022) - [i87]Kelly W. Zhang, Omer Gottesman, Finale Doshi-Velez:
A Bayesian Approach to Learning Bandit Structure in Markov Decision Processes. CoRR abs/2208.00250 (2022) - [i86]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 abs/2208.01705 (2022) - [i85]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 abs/2208.07406 (2022) - [i84]Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju:
Towards Robust Off-Policy Evaluation via Human Inputs. CoRR abs/2209.08682 (2022) - [i83]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:
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. CoRR abs/2210.15767 (2022) - [i82]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 abs/2211.05667 (2022) - [i81]Sanjana Narayanan, Isaac Lage, Finale Doshi-Velez:
(When) Are Contrastive Explanations of Reinforcement Learning Helpful? CoRR abs/2211.07719 (2022) - [i80]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 abs/2211.09184 (2022) - [i79]Eura Shin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Modeling Mobile Health Users as Reinforcement Learning Agents. CoRR abs/2212.00863 (2022) - 2021
- [j18]Been Kim, Finale Doshi-Velez:
Machine Learning Techniques for Accountability. AI Mag. 42(1): 47-52 (2021) - [j17]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): 181-216 (2021) - [j16]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: 1-37 (2021) - [c74]Nari Johnson, Sonali Parbhoo, Andrew Slavin Ross, Finale Doshi-Velez:
Learning Predictive and Interpretable Timeseries Summaries from ICU Data. AMIA 2021 - [c73]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: 80:1-80:15 - [c72]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:
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens. CHI 2021: 659:1-659:14 - [c71]Andrew Slavin Ross, Finale Doshi-Velez:
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement. ICML 2021: 9084-9094 - [c70]Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez:
State Relevance for Off-Policy Evaluation. ICML 2021: 9537-9546 - [c69]Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Power Constrained Bandits. MLHC 2021: 209-259 - [c68]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: 8795-8806 - [c67]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: 14-18 - [i78]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 abs/2101.03309 (2021) - [i77]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 abs/2101.05360 (2021) - [i76]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:
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens. CoRR abs/2102.00593 (2021) - [i75]Andrew Slavin Ross, Nina Chen, Elisa Zhao Hang, Elena L. Glassman, Finale Doshi-Velez:
Evaluating the Interpretability of Generative Models by Interactive Reconstruction. CoRR abs/2102.01264 (2021) - [i74]Andrew Slavin Ross, Finale Doshi-Velez:
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement. CoRR abs/2102.05185 (2021) - [i73]Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju:
Learning Under Adversarial and Interventional Shifts. CoRR abs/2103.15933 (2021) - [i72]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 abs/2106.03279 (2021) - [i71]Beau Coker, Weiwei Pan, Finale Doshi-Velez:
Wide Mean-Field Variational Bayesian Neural Networks Ignore the Data. CoRR abs/2106.07052 (2021) - [i70]Anita Mahinpei, Justin Clark, Isaac Lage, Finale Doshi-Velez, Weiwei Pan:
Promises and Pitfalls of Black-Box Concept Learning Models. CoRR abs/2106.13314 (2021) - [i69]Eura Shin, Pedja Klasnja, Susan A. Murphy, Finale Doshi-Velez:
Online structural kernel selection for mobile health. CoRR abs/2107.09949 (2021) - [i68]Simon P. Shen, Yecheng Jason Ma, Omer Gottesman, Finale Doshi-Velez:
State Relevance for Off-Policy Evaluation. CoRR abs/2109.06310 (2021) - [i67]Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez:
Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty. CoRR abs/2109.06312 (2021) - [i66]Sarah Rathnam, Susan A. Murphy, Finale Doshi-Velez:
Comparison and Unification of Three Regularization Methods in Batch Reinforcement Learning. CoRR abs/2109.08134 (2021) - [i65]Nari Johnson, Sonali Parbhoo, Andrew Slavin Ross, Finale Doshi-Velez:
Learning Predictive and Interpretable Timeseries Summaries from ICU Data. CoRR abs/2109.11043 (2021) - [i64]Abhishek Sharma, Catherine Zeng, Sanjana Narayanan, Sonali Parbhoo, Finale Doshi-Velez:
On Learning Prediction-Focused Mixtures. CoRR abs/2110.13221 (2021) - [i63]Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill:
Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation. CoRR abs/2111.14272 (2021) - 2020
- [c66]Andrew Slavin Ross, Weiwei Pan, Leo A. Celi, Finale Doshi-Velez:
Ensembles of Locally Independent Prediction Models. AAAI 2020: 5527-5536 - [c65]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: 6413-6421 - [c64]Joseph Futoma, Michael C. Hughes, Finale Doshi-Velez:
POPCORN: Partially Observed Prediction Constrained Reinforcement Learning. AISTATS 2020: 3578-3588 - [c63]Jason Ren, Russell Kunes, Finale Doshi-Velez:
Prediction Focused Topic Models via Feature Selection. AISTATS 2020: 4420-4429 - [c62]Mingyu Lu, Zachary Shahn, Daby Sow, Finale Doshi-Velez, Li-Wei H. Lehman:
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients. AMIA 2020 - [c61]Niranjani Prasad, Barbara E. Engelhardt, Finale Doshi-Velez:
Defining admissible rewards for high-confidence policy evaluation in batch reinforcement learning. CHIL 2020: 1-9 - [c60]Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo A. Celi, Emma Brunskill, Finale Doshi-Velez:
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. ICML 2020: 3658-3667 - [c59]Han-Ching Ou, Kai Wang, Finale Doshi-Velez, Milind Tambe:
Active Screening on Recurrent Diseases Contact Networks with Uncertainty: A Reinforcement Learning Approach. MABS 2020: 54-65 - [c58]Sonali Parbhoo, Mario Wieser, Volker Roth, Finale Doshi-Velez:
Transfer Learning from Well-Curated to Less-Resourced Populations with HIV. MLHC 2020: 589-609 - [c57]Jianzhun Du, Joseph Futoma, Finale Doshi-Velez:
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs. NeurIPS 2020 - [c56]Wanqian Yang, Lars Lorch, Moritz A. Graule, Himabindu Lakkaraju, Finale Doshi-Velez:
Incorporating Interpretable Output Constraints in Bayesian Neural Networks. NeurIPS 2020 - [c55]Beau Coker, Melanie Fernandes Pradier, Finale Doshi-Velez:
PoRB-Nets: Poisson Process Radial Basis Function Networks. UAI 2020: 1338-1347 - [e6]Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens:
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2020, 7-8 August 2020, Virtual Event, Durham, NC, USA. Proceedings of Machine Learning Research 126, PMLR 2020 [contents] - [i62]Joseph Futoma, Muhammad A. Masood, Finale Doshi-Velez:
Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning. CoRR abs/2001.03224 (2020) - [i61]Joseph Futoma, Michael C. Hughes, Finale Doshi-Velez:
POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning. CoRR abs/2001.04032 (2020) - [i60]Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Anthony Celi, Emma Brunskill, Finale Doshi-Velez:
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. CoRR abs/2002.03478 (2020) - [i59]Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez:
Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders. CoRR abs/2003.07756 (2020) - [i58]Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Power-Constrained Bandits. CoRR abs/2004.06230 (2020) - [i57]Mingyu Lu,