Finale Doshi-Velez

发表

Spoken language interaction with model uncertainty: an adaptive human–robot interaction system

Nicholas Roy, Finale Doshi-Velez, N. Roy, 2008, Connect. Sci..

Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors

Finale Doshi-Velez, Soumya Ghosh, Jiayu Yao, 2018, ICML.

Bayesian nonparametric approaches for reinforcement learning in partially observable domains

Nicholas Roy, Finale Doshi-Velez, N. Roy, 2012 .

Zoubin Ghahramani, Finale Doshi-Velez, Zoubin Ghahramani, 2009, UAI.

Nonparametric Bayesian Approaches for Reinforcement Learning in Partially Observable Domains

Finale Doshi-Velez, 2010, AAAI.

Variational Inference for the Indian Buffet Process

Yee Whye Teh, Finale Doshi-Velez, Kurt Miller, 2009, AISTATS.

Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders pdf

Finale Doshi-Velez, Weiwei Pan, Yaniv Yacoby, 2020, AABI.

Memory-Bounded Left-Corner Unsupervised Grammar Induction on Child-Directed Input

Lane Schwartz, Finale Doshi-Velez, William Schuler, 2016, COLING.

Learned Uncertainty-Aware (LUNA) Bases for Bayesian Regression using Multi-Headed Auxiliary Networks pdf

Finale Doshi-Velez, Yaniv Yacoby, Sujay Thakur, 2020, ArXiv.

Incorporating Interpretable Output Constraints in Bayesian Neural Networks pdf

Finale Doshi-Velez, Himabindu Lakkaraju, Wanqian Yang, 2020, NeurIPS.

Accountability of AI Under the Law: The Role of Explanation pdf

David Weinberger, Finale Doshi-Velez, Mason Kortz, 2017, ArXiv.

Promoting Domain-Specific Terms in Topic Models with Informative Priors pdf

Luke Miratrix, Finale Doshi-Velez, Angela Fan, 2017, ArXiv.

Model Selection in Bayesian Neural Networks via Horseshoe Priors

Soumya Ghosh, Finale Doshi-Velez, Jiayu Yao, 2017, J. Mach. Learn. Res..

多軸光力センサにおける環境外乱除去への機械学習アプローチ【Powered by NICT】

Robert J. Wood, Conor J. Walsh, Finale Doshi-Velez, 2016 .

Exploring Computational User Models for Agent Policy Summarization pdf

Finale Doshi-Velez, Ofra Amir, Isaac Lage, 2019, IJCAI.

Representation Balancing MDPs for Off-Policy Policy Evaluation

Yao Liu, Finale Doshi-Velez, Emma Brunskill, 2018, NeurIPS.

Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process

Zoubin Ghahramani, Finale Doshi-Velez, David A. Knowles, 2009, NIPS.

PAC Bounds for Imitation and Model-based Batch Learning of Contextual Markov Decision Processes pdf

Finale Doshi-Velez, Yash Nair, 2020, ArXiv.

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients

Finale Doshi-Velez, Daby Sow, MingYu Lu, 2020, AMIA.

Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction

Finale Doshi-Velez, Been Kim, Julie A. Shah, 2015, NIPS.

The Indian Buffet Process: Scalable Inference and Extensions

Finale Doshi-Velez, Finale Doshi-Velez, 2009 .

Accelerated sampling for the Indian Buffet Process

Zoubin Ghahramani, Finale Doshi-Velez, Zoubin Ghahramani, 2009, ICML '09.

Graph-Sparse LDA: A Topic Model with Structured Sparsity

Ryan P. Adams, Byron C. Wallace, Finale Doshi-Velez, 2014, AAAI.

A Roadmap for a Rigorous Science of Interpretability pdf

Finale Doshi-Velez, Been Kim, Finale Doshi-Velez, 2017, ArXiv.

The Infinite Partially Observable Markov Decision Process

Finale Doshi-Velez, Finale Doshi-Velez, F. Doshi-Velez, 2009, NIPS.

Combining Kernel and Model Based Learning for HIV Therapy Selection

Finale Doshi-Velez, Volker Roth, Jasmina Bogojeska, 2017, CRI.

The permutable POMDP: fast solutions to POMDPs for preference elicitation

Nicholas Roy, Finale Doshi-Velez, N. Roy, 2008, AAMAS.

Power-Constrained Bandits pdf

Finale Doshi-Velez, Weiwei Pan, Susan Murphy, 2020, MLHC.

Organizing committee

Finale Doshi-Velez, Paul Cuddihy, Mark Buller, 2000, Clinical Neurophysiology.

Hidden Parameter Markov Decision Processes: An Emerging Paradigm for Modeling Families of Related Tasks

Finale Doshi-Velez, George Konidaris, G. Konidaris, 2014, AAAI Fall Symposia.

Efficient model learning for dialog management

Nicholas Roy, Finale Doshi-Velez, N. Roy, 2007, 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI).

Ensembles of Locally Independent Prediction Models

Finale Doshi-Velez, Weiwei Pan, Leo Anthony Celi, 2020, AAAI.

Collision detection in legged locomotion using supervised learning

Nicholas Roy, Finale Doshi-Velez, Emma Brunskill, 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Reports of the AAAI 2011 Spring Symposia

Nancy Green, Knut Hinkelmann, Dylan A. Shell, 2011, AI Mag..

Assessing topic model relevance: Evaluation and informative priors

Luke Miratrix, Finale Doshi-Velez, Angela Fan, 2019, Stat. Anal. Data Min..

Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations

Finale Doshi-Velez, George Konidaris, G. Konidaris, 2013, IJCAI.

Depth-bounding is effective: Improvements and evaluation of unsupervised PCFG induction pdf

Lane Schwartz, Finale Doshi-Velez, William Schuler, 2018, EMNLP.

A Bayesian nonparametric approach to modeling motion patterns

Albert S. Huang, Nicholas Roy, Finale Doshi-Velez, 2011, Auton. Robots.

Semi-Supervised Prediction-Constrained Topic Models

Finale Doshi-Velez, Erik B. Sudderth, Michael C. Hughes, 2018, AISTATS.

Learning Interpretable Concept-Based Models with Human Feedback pdf

Finale Doshi-Velez, Isaac Lage, Finale Doshi-Velez, 2020, ArXiv.

Prediction-Constrained Topic Models for Antidepressant Recommendation pdf

Finale Doshi-Velez, Erik B. Sudderth, Michael C. Hughes, 2017, ArXiv.

Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs pdf

Finale Doshi-Velez, Joseph Futoma, Jianzhun Du, 2020, NeurIPS.

Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning

Andrew Slavin Ross, Finale Doshi-Velez, Li-Wei H. Lehman, 2018, AMIA.

Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks pdf

Finale Doshi-Velez, Yaniv Yacoby, Weiwei Pan, 2020, ArXiv.

Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs

Joelle Pineau, Nicholas Roy, Finale Doshi-Velez, 2008, ICML '08.

Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning

David Pfau, Frank D. Wood, Nicholas Roy, 2015, IEEE Trans. Pattern Anal. Mach. Intell..

Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible pdf

Javier Zazo, Finale Doshi-Velez, Melanie F. Pradier, 2021, ArXiv.

Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks pdf

Finale Doshi-Velez, Melanie F. Pradier, Beau Coker, 2019, ArXiv.

Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters pdf

Yao Liu, Finale Doshi-Velez, Emma Brunskill, 2018, ArXiv.

How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation pdf

Emily Chen, Finale Doshi-Velez, Been Kim, 2018, ArXiv.

Nonparametric Bayesian Policy Priors for Reinforcement Learning

Joshua B. Tenenbaum, Nicholas Roy, Finale Doshi-Velez, 2010, NIPS.

Infinite Dynamic Bayesian Networks

Joshua B. Tenenbaum, Nicholas Roy, Finale Doshi-Velez, 2011, ICML.

Transfer Learning by Discovering Latent Task Parametrizations

Finale Doshi-Velez, George Konidaris, 2012, NIPS 2012.

Unsupervised Grammar Induction with Depth-bounded PCFG

Lane Schwartz, Finale Doshi-Velez, William Schuler, 2018, TACL.

Roll-back Hamiltonian Monte Carlo

Kexin Yi, Finale Doshi-Velez, Kexin Yi, 2017, 1709.02855.

Combining Parametric and Nonparametric Models for Off-Policy Evaluation

Yao Liu, Finale Doshi-Velez, Emma Brunskill, 2019, ICML.

Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice

Pavlos Protopapas, Finale Doshi-Velez, Xide Xia, 2016, SDM.

Regional Tree Regularization for Interpretability in Black Box Models pdf

Mike Wu, Finale Doshi-Velez, Volker Roth, 2019, ArXiv.

Predicting intervention onset in the ICU with switching state space models

Peter Szolovits, Mike Wu, Finale Doshi-Velez, 2017, CRI.

A Bayesian Framework for Learning Rule Sets for Interpretable Classification

Cynthia Rudin, Finale Doshi-Velez, Tong Wang, 2017, J. Mach. Learn. Res..

Human-in-the-Loop Interpretability Prior

Samuel J. Gershman, Finale Doshi-Velez, Been Kim, 2018, NeurIPS.

Spectral M-estimation with Applications to Hidden Markov Models pdf

Dustin Tran, Finale Doshi-Velez, Minjae Kim, 2016, AISTATS.

Toward Robust Policy Summarization

Finale Doshi-Velez, Ofra Amir, Isaac Lage, 2019, AAMAS.

An Empirical Comparison of Sampling Quality Metrics: A Case Study for Bayesian Nonnegative Matrix Factorization pdf

Finale Doshi-Velez, Weiwei Pan, Arjumand Masood, 2016, ArXiv.

PoRB-Nets: Poisson Process Radial Basis Function Networks

Finale Doshi-Velez, Beau Coker, Melanie Fernandes Pradier, 2020, UAI.

Regional Tree Regularization for Interpretability in Deep Neural Networks

Mike Wu, Finale Doshi-Velez, Volker Roth, 2020, AAAI.

Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies pdf

Finale Doshi-Velez, Muhammad A. Masood, Finale Doshi-Velez, 2019, IJCAI.

Interpretable Batch IRL to Extract Clinician Goals in ICU Hypotension Management.

Srivatsan Srinivasan, Finale Doshi-Velez, 2020, AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science.

Prediction-Constrained Training for Semi-Supervised Mixture and Topic Models pdf

Finale Doshi-Velez, Erik B. Sudderth, Michael C. Hughes, 2017, ArXiv.

A general method for regularizing tensor decomposition methods via pseudo-data pdf

Finale Doshi-Velez, Weiwei Pan, Omer Gottesman, 2019, ArXiv.

POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning pdf

Finale Doshi-Velez, Michael C. Hughes, Joseph Futoma, 2020, AISTATS.

Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients

Andrew Slavin Ross, Finale Doshi-Velez, Finale Doshi-Velez, 2017, AAAI.

Unfolding physiological state: mortality modelling in intensive care units

Anna Rumshisky, Peter Szolovits, Finale Doshi-Velez, 2014, KDD.

Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes pdf

George Dimitri Konidaris, Finale Doshi-Velez, Taylor W. Killian, 2016, ArXiv.

A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations pdf

Finale Doshi-Velez, Weiwei Pan, Weiwei Pan, 2016, ArXiv.

Machine learning approaches to environmental disturbance rejection in multi-axis optoelectronic force sensors

Robert J. Wood, Conor J. Walsh, Finale Doshi-Velez, 2016 .

A Particle-Based Variational Approach to Bayesian Non-negative Matrix Factorization

Finale Doshi-Velez, Muhammad A. Masood, M. A. Masood, 2018, J. Mach. Learn. Res..

Defining admissible rewards for high-confidence policy evaluation in batch reinforcement learning

Finale Doshi-Velez, Barbara E. Engelhardt, Niranjani Prasad, 2020, CHIL.

Bayesian Rule Sets for Interpretable Classification

Cynthia Rudin, Finale Doshi-Velez, Tong Wang, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

BaCOUn: Bayesian Classifers with Out-of-Distribution Uncertainty pdf

Finale Doshi-Velez, Yaniv Yacoby, Weiwei Pan, 2020, ArXiv.

Truly Batch Apprenticeship Learning with Deep Successor Features pdf

Srivatsan Srinivasan, Finale Doshi-Velez, Donghun Lee, 2019, IJCAI.

Evaluating Reinforcement Learning Algorithms in Observational Health Settings pdf

Srivatsan Srinivasan, Finale Doshi-Velez, Li-Wei H. Lehman, 2018, ArXiv.

Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning

Finale Doshi-Velez, Steffen Udluft, José Miguel Hernández-Lobato, 2017, ICML.

Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks pdf

Finale Doshi-Velez, Steffen Udluft, José Miguel Hernández-Lobato, 2016, ICLR.

Unsupervised Learning of PCFGs with Normalizing Flow

Lane Schwartz, Finale Doshi-Velez, William Schuler, 2019, ACL.

Latent Projection BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights pdf

Finale Doshi-Velez, Weiwei Pan, Soumya Ghosh, 2018, ArXiv.

A Comparison of Human and Agent Reinforcement Learning in Partially Observable Domains

Zoubin Ghahramani, Finale Doshi-Velez, Zoubin Ghahramani, 2011, CogSci.

Quality of Uncertainty Quantification for Bayesian Neural Network Inference pdf

Soumya Ghosh, Finale Doshi-Velez, Weiwei Pan, 2019, ArXiv.

Prediction Focused Topic Models via Vocab Selection pdf

Finale Doshi-Velez, Jason Ren, Russell Kunes, 2019, ArXiv.

Agent Strategy Summarization

David Sarne, Finale Doshi-Velez, Ofra Amir, 2018, AAMAS.

Beyond Sparsity: Tree Regularization of Deep Models for Interpretability

Mike Wu, Finale Doshi-Velez, Volker Roth, 2017, AAAI.

Online Discovery of Feature Dependencies

Alborz Geramifard, Jonathan P. How, Joshua D. Redding, 2011, ICML.

Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes

Finale Doshi-Velez, George Konidaris, Taylor W. Killian, 2017, AAAI.

PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models

Daniel J. Wigdor, Finale Doshi-Velez, Mahdi Pakdaman Naeini, 2018, IEEE Transactions on Visualization and Computer Graphics.

Computational physiology : papers from the AAAI Spring Symposium

Finale Doshi-Velez, Paul Edward Cuddihy, Mark J. Buller, 2011 .

Weighted Tensor Decomposition for Learning Latent Variables with Partial Data

Finale Doshi-Velez, Weiwei Pan, Omer Gottesman, 2018, AISTATS.

Restricted Indian buffet processes

Finale Doshi-Velez, Sinead Williamson, 2017, Stat. Comput..

A Bayesian Nonparametric Approach to Modeling Mobility Patterns

Nicholas Roy, Finale Doshi-Velez, Joshua Mason Joseph, 2010, AAAI.

Learning Qualitatively Diverse and Interpretable Rules for Classification pdf

Andrew Slavin Ross, Finale Doshi-Velez, Weiwei Pan, 2018, ArXiv.

Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems pdf

Yimin Liu, Tong Wang, Cynthia Rudin, 2015, ArXiv.

Decomposition of Uncertainty for Active Learning and Reliable Reinforcement Learning in Stochastic Systems pdf

Finale Doshi-Velez, Steffen Udluft, José Miguel Hernández-Lobato, 2017, ArXiv.

Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations

Andrew Slavin Ross, Finale Doshi-Velez, Michael C. Hughes, 2017, IJCAI.

The application of machine learning methods to evaluate predictors of live birth in programmed thaw cycles

Finale Doshi-Velez, Weiwei Pan, Yaniv Yacoby, 2019 .

Identifying Decision Points for Safe and Interpretable Reinforcement Learning in Hypotension Treatment pdf

Finale Doshi-Velez, Leo Anthony Celi, Brian Chu, 2021, ArXiv.

Output-Constrained Bayesian Neural Networks pdf

Srivatsan Srinivasan, Finale Doshi-Velez, Wanqian Yang, 2019, ArXiv.

Learning Deep Bayesian Latent Variable Regression Models that Generalize: When Non-identifiability is a Problem pdf

Finale Doshi-Velez, Weiwei Pan, Yaniv Yacoby, 2019, ArXiv.

Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models pdf

Finale Doshi-Velez, Viktoriya Krakovna, Viktoriya Krakovna, 2016, ArXiv.

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Sepsis Treatment pdf

Finale Doshi-Velez, Daby Sow, MingYu Lu, 2020, ArXiv.

Optimizing for Interpretability in Deep Neural Networks with Tree Regularization pdf

Mike Wu, Finale Doshi-Velez, Volker Roth, 2019, J. Artif. Intell. Res..

A Bayesian nonparametric approach to modeling battery health

Nicholas Roy, Finale Doshi-Velez, Joshua Mason Joseph, 2012, 2012 IEEE International Conference on Robotics and Automation.

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning pdf

Finale Doshi-Velez, Milind Tambe, Andrew Perrault, 2021, ArXiv.

Wide Mean-Field Variational Bayesian Neural Networks Ignore the Data pdf

Finale Doshi-Velez, Weiwei Pan, Beau Coker, 2021, ArXiv.

Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making

Finale Doshi-Velez, Shalmali Joshi, Sonali Parbhoo, 2022, ArXiv.

Evaluating the Interpretability of Generative Models by Interactive Reconstruction

Elena L. Glassman, Finale Doshi-Velez, Nina Chen, 2021, CHI.

Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation

Finale Doshi-Velez, Emma Brunskill, Leo Anthony Celi, 2021, CHIL.

Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty pdf

Finale Doshi-Velez, Shalmali Joshi, Sonali Parbhoo, 2021, ArXiv.

On Learning Prediction-Focused Mixtures pdf

Finale Doshi-Velez, Sonali Parbhoo, Abhishek Sharma, 2021, ArXiv.

Machine Learning Techniques for Accountability

Finale Doshi-Velez, Been Kim, Been Kim, 2021, AI Mag..

Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens

Krzysztof Z. Gajos, Finale Doshi-Velez, Maia Jacobs, 2021, CHI.

Promises and Pitfalls of Black-Box Concept Learning Models pdf

Finale Doshi-Velez, Weiwei Pan, Isaac Lage, 2021, ArXiv.

Online structural kernel selection for mobile health pdf

Finale Doshi-Velez, Susan Murphy, Pedja Klasnja, 2021, ArXiv.

Learning Under Adversarial and Interventional Shifts pdf

Finale Doshi-Velez, Himabindu Lakkaraju, Shalmali Joshi, 2021, ArXiv.

Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement

Finale Doshi-Velez, Andrew Slavin Ross, 2021, ICML.

Learning Predictive and Interpretable Timeseries Summaries from ICU Data pdf

Finale Doshi-Velez, Sonali Parbhoo, Andrew Slavin Ross, 2021, AMIA.

Depth-Bounded Statistical PCFG Induction as a Model of Human Grammar Acquisition

Lane Schwartz, Finale Doshi-Velez, William Schuler, 2021, CL.

Comparison and Unification of Three Regularization Methods in Batch Reinforcement Learning pdf

Susan A. Murphy, Finale Doshi-Velez, Sarah Rathnam, 2021, ArXiv.

State Relevance for Off-Policy Evaluation

Finale Doshi-Velez, Omer Gottesman, Simon P. Shen, 2021, ICML.

Learned Uncertainty-Aware (LUNA) Bases for Bayesian Regression using Multi-Headed Auxiliary Networks pdf

Finale Doshi-Velez, Weiwei Pan, Yaniv Yacoby, 2020, ArXiv.

Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions

Yao Liu, Finale Doshi-Velez, Emma Brunskill, 2020, ICML.

Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder

Finale Doshi-Velez, Pei Chen, Joseph Bochenek, 2016, PloS one.