Chih-Kuan Yeh
Chih-Kuan Yeh
Google Brain
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On the (In)fidelity and Sensitivity for Explanations
CK Yeh, CY Hsieh, AS Suggala, D Inouye, P Ravikumar
Advances in Neural Information Processing Systems, 2019, 2019
Multi-label zero-shot learning with structured knowledge graphs
CW Lee, W Fang, CK Yeh, YCF Wang
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Learning Deep Latent Spaces for Multi-Label Classification.
CK Yeh, WC Wu, WJ Ko, YCF Wang
AAAI, 2838-2844, 2017
On Completeness-Aware Concept-Based Explanations in Deep Neural Networks
CK Yeh, B Kim, SO Arik, CL Li, T Pfister, P Ravikumar
Advances in Neural Information Processing Systems, 2020, 2020
Representer point selection for explaining deep neural networks
CK Yeh, J Kim, IEH Yen, PK Ravikumar
Advances in neural information processing systems, 2018, 9291-9301, 2018
Order-free rnn with visual attention for multi-label classification
SF Chen, YC Chen, CK Yeh, YC Wang
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
Automatic bridge bidding using deep reinforcement learning
CK Yeh, CY Hsieh, HT Lin
IEEE Transactions on Games 10 (4), 365-377, 2018
Evaluations and methods for explanation through robustness analysis
CY Hsieh, CK Yeh, X Liu, P Ravikumar, S Kim, S Kumar, CJ Hsieh
International Conference on Representation Learning 2021, 2020
Minimizing flops to learn efficient sparse representations
B Paria, CK Yeh, IEH Yen, N Xu, P Ravikumar, B Póczos
International Conference on Learning Representation 2020, 2020
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
CK Yeh, J Chen, C Yu, D Yu
International Conference on Representation Learning 2019, 2018
Deep generative models for weakly-supervised multi-label classification
HM Chu, CK Yeh, YCF Wang
Proceedings of the European Conference on Computer Vision (ECCV), 400-415, 2018
Distilling step-by-step! outperforming larger language models with less training data and smaller model sizes
CY Hsieh, CL Li, CK Yeh, H Nakhost, Y Fujii, A Ratner, R Krishna, CY Lee, ...
arXiv preprint arXiv:2305.02301, 2023
Human-Centered Concept Explanations for Neural Networks
CK Yeh, B Kim, P Ravikumar
IOS Press, 2022
Faith-Shap: The Faithful Shapley Interaction Index
CP Tsai, CK Yeh, P Ravikumar
arXiv preprint arXiv:2203.00870, 2022
Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations
CK Yeh, KY Lee, F Liu, P Ravikumar
International Conference on Artificial Intelligence and Statistics 2022, 2022
First is Better Than Last for Language Data Influence
CK Yeh, A Taly, M Sundararajan, F Liu, P Ravikumar
arXiv preprint arXiv:2202.11844, 2022
Concept Gradient: Concept-based Interpretation Without Linear Assumption
A Bai, CK Yeh, P Ravikumar, NYC Lin, CJ Hsieh
arXiv preprint arXiv:2208.14966, 2022
Objective criteria for explanations of machine learning models
CK Yeh, P Ravikumar
Applied AI Letters 2 (4), e57, 2021
Unsupervised automatic speech recognition
J Chen, YU Chengzhu, D Yu, CK Yeh
US Patent 11,138,966, 2021
Objective Criteria for Explainable Machine Learning
CK Yeh
Carnegie Mellon University, 2022
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