Ian Covert

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 20

Top Topics

Conditional Mutual Information

Granger Causality

Locally Weighted

Feature Selection

Top Venues

J. Mach. Learn. Res.

Publications

Ian Covert, Chanwoo Kim, Su-In Lee, James Zou, Tatsunori Hashimoto
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution. CoRR (2024)
Ian Covert, Wenlong Ji, Tatsunori Hashimoto, James Zou
Scaling Laws for the Value of Individual Data Points in Machine Learning. CoRR (2024)
Chris Lin, Ian Covert, Su-In Lee
On the Robustness of Removal-Based Feature Attributions. NeurIPS (2023)
Chris Lin, Ian Covert, Su-In Lee
On the Robustness of Removal-Based Feature Attributions. CoRR (2023)
Sarah M. Pratt, Ian Covert, Rosanne Liu, Ali Farhadi
What does a platypus look like? Generating customized prompts for zero-shot image classification. ICCV (2023)
Soham Gadgil, Ian Covert, Su-In Lee
Estimating Conditional Mutual Information for Dynamic Feature Selection. CoRR (2023)
Ethan Weinberger, Ian Covert, Su-In Lee
Feature Selection in the Contrastive Analysis Setting. NeurIPS (2023)
Ian Covert, Wei Qiu, Mingyu Lu, Nayoon Kim, Nathan White, Su-In Lee
Learning to Maximize Mutual Information for Dynamic Feature Selection. CoRR (2023)
Ethan Weinberger, Ian Covert, Su-In Lee
Feature Selection in the Contrastive Analysis Setting. CoRR (2023)
Alex Tank, Ian Covert, Nicholas J. Foti, Ali Shojaie, Emily B. Fox
Neural Granger Causality. IEEE Trans. Pattern Anal. Mach. Intell. 44 (8) (2022)
Ian Covert, Chanwoo Kim, Su-In Lee
Learning to Estimate Shapley Values with Vision Transformers. CoRR (2022)
Ivan Evtimov, Ian Covert, Aditya Kusupati, Tadayoshi Kohno
Disrupting Model Training with Adversarial Shortcuts. CoRR (2021)
Ian Covert, Su-In Lee
Improving KernelSHAP: Practical Shapley Value Estimation Using Linear Regression. AISTATS (2021)
Ian Covert, Scott M. Lundberg, Su-In Lee
Explaining by Removing: A Unified Framework for Model Explanation. J. Mach. Learn. Res. 22 (2021)
Neil Jethani, Mukund Sudarshan, Ian Covert, Su-In Lee, Rajesh Ranganath
FastSHAP: Real-Time Shapley Value Estimation. CoRR (2021)
Ian Covert, Scott M. Lundberg, Su-In Lee
Understanding Global Feature Contributions Through Additive Importance Measures. CoRR (2020)
Ian Covert, Su-In Lee
Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression. CoRR (2020)
Ian Covert, Scott M. Lundberg, Su-In Lee
Feature Removal Is a Unifying Principle for Model Explanation Methods. CoRR (2020)
Ian Covert, Scott M. Lundberg, Su-In Lee
Understanding Global Feature Contributions With Additive Importance Measures. NeurIPS (2020)
Ian Covert, Scott M. Lundberg, Su-In Lee
Explaining by Removing: A Unified Framework for Model Explanation. CoRR (2020)