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Concept Gradient: Concept-based Interpretation Without Linear Assumption


Aug 31, 2022
Andrew Bai, Chih-Kuan Yeh, Pradeep Ravikumar, Neil Y. C. Lin, Cho-Jui Hsieh

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Faith-Shap: The Faithful Shapley Interaction Index


Mar 09, 2022
Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar

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Human-Centered Concept Explanations for Neural Networks


Feb 25, 2022
Chih-Kuan Yeh, Been Kim, Pradeep Ravikumar

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* book chapter of Neuro-Symbolic Artificial Intelligence: The State of the Art, volume: 342, p.337 - 352, 2022 

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Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations


Feb 24, 2022
Chih-Kuan Yeh, Kuan-Yun Lee, Frederick Liu, Pradeep Ravikumar

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* AISTATS 2022 

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First is Better Than Last for Training Data Influence


Feb 24, 2022
Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep Ravikumar

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Evaluations and Methods for Explanation through Robustness Analysis


May 31, 2020
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh

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Minimizing FLOPs to Learn Efficient Sparse Representations


Apr 12, 2020
Biswajit Paria, Chih-Kuan Yeh, Ian E. H. Yen, Ning Xu, Pradeep Ravikumar, Barnabás Póczos

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* Published at ICLR 2020 

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On Concept-Based Explanations in Deep Neural Networks


Oct 17, 2019
Chih-Kuan Yeh, Been Kim, Sercan O. Arik, Chun-Liang Li, Pradeep Ravikumar, Tomas Pfister

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How Sensitive are Sensitivity-Based Explanations?


Jan 27, 2019
Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David Inouye, Pradeep Ravikumar

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Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching


Dec 23, 2018
Chih-Kuan Yeh, Jianshu Chen, Chengzhu Yu, Dong Yu

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* Published as a conference paper at ICLR 2019 

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