Oscar Li

发表

This Looks Like That: Deep Learning for Interpretable Image Recognition

Cynthia Rudin, Jonathan Su, Chaofan Chen, 2018 .

Is Support Set Diversity Necessary for Meta-Learning? pdf

Virginia Smith, Amrith Setlur, Amrith Rajagopal Setlur, 2020, ArXiv.

Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains its Predictions

Cynthia Rudin, Chaofan Chen, Hao Liu, 2017, AAAI.

Interpretable Image Recognition with Hierarchical Prototypes pdf

Cynthia Rudin, Chaofan Chen, Oscar Li, 2019, HCOMP.

Lessons from Chasing Few-Shot Learning Benchmarks: Rethinking the Evaluation of Meta-Learning Methods pdf

Virginia Smith, Amrith Setlur, Amrith Rajagopal Setlur, 2021, ArXiv.

Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution

Amrith Rajagopal Setlur, Virginia Smith, Oscar Li, 2021, NeurIPS.

Label Leakage and Protection in Two-party Split Learning

Virginia Smith, Hongyi Zhang, Junyuan Xie, 2021, ICLR.

Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains its Predictions

Hao Liu, C. Rudin, Oscar Li, 2017, AAAI.

This looks like that: deep learning for interpretable image recognition

C. Rudin, Oscar Li, Jonathan Su, 2018, NeurIPS.

Noise-Reuse in Online Evolution Strategies

Virginia Smith, Luke Metz, Oscar Li, 2023, ArXiv.

Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies

Virginia Smith, Luke Metz, Oscar Li, 2023, NeurIPS.