Isaac Lage

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 14

Top Topics

Eligibility Traces

Reinforcement Learning

Learning Models

Top Venues

Trans. Mach. Learn. Res.

Publications

Isaac Lage, Sonali Parbhoo, Finale Doshi-Velez
Towards Integrating Personal Knowledge into Test-Time Predictions. CoRR (2024)
Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage, Himabindu Lakkaraju
When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making. Trans. Mach. Learn. Res. 2023 (2023)
Sanjana Narayanan, Isaac Lage, Finale Doshi-Velez
(When) Are Contrastive Explanations of Reinforcement Learning Helpful? CoRR (2022)
Anita Mahinpei, Justin Clark, Isaac Lage, Finale Doshi-Velez, Weiwei Pan
Promises and Pitfalls of Black-Box Concept Learning Models. CoRR (2021)
Isaac Lage, Finale Doshi-Velez
Learning Interpretable Concept-Based Models with Human Feedback. CoRR (2020)
Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage, Himabindu Lakkaraju
When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making. CoRR (2020)
Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, Ofra Amir
Toward Robust Policy Summarization. AAMAS (2019)
Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, Ofra Amir
Exploring Computational User Models for Agent Policy Summarization. CoRR (2019)
Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Samuel J. Gershman, Finale Doshi-Velez
Human Evaluation of Models Built for Interpretability. HCOMP (2019)
Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, Ofra Amir
Exploring Computational User Models for Agent Policy Summarization. IJCAI (2019)
Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Sam Gershman, Finale Doshi-Velez
An Evaluation of the Human-Interpretability of Explanation. CoRR (2019)
Isaac Lage, Andrew Slavin Ross, Been Kim, Samuel J. Gershman, Finale Doshi-Velez
Human-in-the-Loop Interpretability Prior. CoRR (2018)
Isaac Lage, Andrew Slavin Ross, Samuel J. Gershman, Been Kim, Finale Doshi-Velez
Human-in-the-Loop Interpretability Prior. NeurIPS (2018)
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
Evaluating Reinforcement Learning Algorithms in Observational Health Settings. CoRR (2018)