Finale Doshi-Velez
Orcid: 0000-0003-2886-3898Affiliations:
- Harvard University, USA
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, USA (former)
According to our database1,
Finale Doshi-Velez
authored at least 176 papers
between 2007 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2024
Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders.
CoRR, 2024
CoRR, 2024
Semi-parametric Expert Bayesian Network Learning with Gaussian Processes and Horseshoe Priors.
CoRR, 2024
Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks.
CoRR, 2024
Proceedings of the 29th International Conference on Intelligent User Interfaces, 2024
2023
CoRR, 2023
Why do universal adversarial attacks work on large language models?: Geometry might be the answer.
CoRR, 2023
Discovering User Types: Mapping User Traits by Task-Specific Behaviors in Reinforcement Learning.
CoRR, 2023
Adaptive interventions for both accuracy and time in AI-assisted human decision making.
CoRR, 2023
The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the 14th International Conference on Ambient Systems, 2023
Reward Design for an Online Reinforcement Learning Algorithm Supporting Oral Self-Care.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
An interpretable RL framework for pre-deployment modeling in ICU hypotension management.
npj Digit. Medicine, 2022
Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables.
J. Mach. Learn. Res., 2022
An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks.
CoRR, 2022
Does the explanation satisfy your needs?: A unified view of properties of explanations.
CoRR, 2022
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report.
CoRR, 2022
CoRR, 2022
CoRR, 2022
Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making.
CoRR, 2022
Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines.
Algorithms, 2022
Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Machine Learning for Healthcare Conference, 2022
"If it didn't happen, why would I change my decision?": How Judges Respond to Counterfactual Explanations for the Public Safety Assessment.
Proceedings of the Tenth AAAI Conference on Human Computation and Crowdsourcing, 2022
Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI.
Proceedings of the Tenth AAAI Conference on Human Computation and Crowdsourcing, 2022
Proceedings of the Conference on Health, Inference, and Learning, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022
Proceedings of the Sixth Workshop on Structured Prediction for NLP, 2022
2021
J. Artif. Intell. Res., 2021
Comparison and Unification of Three Regularization Methods in Batch Reinforcement Learning.
CoRR, 2021
Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty.
CoRR, 2021
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning.
CoRR, 2021
Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible.
CoRR, 2021
Identifying Decision Points for Safe and Interpretable Reinforcement Learning in Hypotension Treatment.
CoRR, 2021
Comput. Linguistics, 2021
Interactive Cohort Analysis and Hypothesis Discovery by Exploring Temporal Patterns in Population-Level Health Records.
Proceedings of the IEEE Workshop on Visual Analytics in Healthcare, 2021
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Machine Learning for Healthcare Conference, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
2020
CoRR, 2020
Learned Uncertainty-Aware (LUNA) Bases for Bayesian Regression using Multi-Headed Auxiliary Networks.
CoRR, 2020
PAC Bounds for Imitation and Model-based Batch Learning of Contextual Markov Decision Processes.
CoRR, 2020
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Sepsis Treatment.
CoRR, 2020
Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning.
CoRR, 2020
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Machine Learning for Healthcare Conference, 2020
Active Screening on Recurrent Diseases Contact Networks with Uncertainty: A Reinforcement Learning Approach.
Proceedings of the Multi-Agent-Based Simulation XXI - 21st International Workshop, 2020
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions.
Proceedings of the 37th International Conference on Machine Learning, 2020
Defining admissible rewards for high-confidence policy evaluation in batch reinforcement learning.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients.
Proceedings of the AMIA 2020, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Stat. Anal. Data Min., 2019
J. Mach. Learn. Res., 2019
J. Mach. Learn. Res., 2019
Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks.
CoRR, 2019
Learning Deep Bayesian Latent Variable Regression Models that Generalize: When Non-identifiability is a Problem.
CoRR, 2019
CoRR, 2019
CoRR, 2019
Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the Seventh AAAI Conference on Human Computation and Crowdsourcing, 2019
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019
Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019
2018
PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models.
IEEE Trans. Vis. Comput. Graph., 2018
Trans. Assoc. Comput. Linguistics, 2018
Latent Projection BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights.
CoRR, 2018
CoRR, 2018
CoRR, 2018
CoRR, 2018
How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation.
CoRR, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018
Depth-bounding is effective: Improvements and Evaluation of Unsupervised PCFG Induction.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018
Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning.
Proceedings of the AMIA 2018, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
J. Mach. Learn. Res., 2017
Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database.
J. Am. Medical Informatics Assoc., 2017
Decomposition of Uncertainty for Active Learning and Reliable Reinforcement Learning in Stochastic Systems.
CoRR, 2017
CoRR, 2017
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks.
Proceedings of the 5th International Conference on Learning Representations, 2017
Proceedings of the Summit on Clinical Research Informatics, 2017
Proceedings of the Summit on Clinical Research Informatics, 2017
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017
2016
J. Mach. Learn. Res., 2016
CoRR, 2016
An Empirical Comparison of Sampling Quality Metrics: A Case Study for Bayesian Nonnegative Matrix Factorization.
CoRR, 2016
Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models.
CoRR, 2016
Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes.
CoRR, 2016
Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016
Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016
Proceedings of the IEEE 16th International Conference on Data Mining, 2016
Proceedings of the COLING 2016, 2016
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
2015
IEEE Trans. Pattern Anal. Mach. Intell., 2015
Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems.
CoRR, 2015
Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
2014
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014
Hidden Parameter Markov Decision Processes: An Emerging Paradigm for Modeling Families of Related Tasks.
Proceedings of the 2014 AAAI Fall Symposia, Arlington, Virginia, USA, November 13-15, 2014, 2014
Proceedings of the Modern Artificial Intelligence for Health Analytics, 2014
2012
Bayesian nonparametric methods for reinforcement learning in partially observable domains.
PhD thesis, 2012
Reinforcement learning with limited reinforcement: Using Bayes risk for active learning in POMDPs.
Artif. Intell., 2012
Proceedings of the IEEE International Conference on Robotics and Automation, 2012
2011
Proceedings of the 28th International Conference on Machine Learning, 2011
Proceedings of the 28th International Conference on Machine Learning, 2011
A Comparison of Human and Agent Reinforcement Learning in Partially Observable Domains.
Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011
2010
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010
Nonparametric Bayesian Approaches for Reinforcement Learning in Partially Observable Domains.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010
2009
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
2008
Spoken language interaction with model uncertainty: an adaptive human-robot interaction system.
Connect. Sci., 2008
Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), 2008
2007
Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 29, 2007
Proceedings of the Multidisciplinary Collaboration for Socially Assistive Robotics, 2007