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On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach


Nov 02, 2022
Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney, Elizabeth M. Daly, Moninder Singh

* Published at NeurIPS 2022 

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PainPoints: A Framework for Language-based Detection of Chronic Pain and Expert-Collaborative Text-Summarization


Sep 14, 2022
Shreyas Fadnavis, Amit Dhurandhar, Raquel Norel, Jenna M Reinen, Carla Agurto, Erica Secchettin, Vittorio Schweiger, Giovanni Perini, Guillermo Cecchi


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Atomist or Holist? A Diagnosis and Vision for More Productive Interdisciplinary AI Ethics Dialogue


Sep 01, 2022
Travis Greene, Amit Dhurandhar, Galit Shmueli

* 9 pages, 1 figure, 2 tables 

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Anomaly Attribution with Likelihood Compensation


Aug 23, 2022
Tsuyoshi Idé, Amit Dhurandhar, Jiří Navrátil, Moninder Singh, Naoki Abe

* 8 pages, 7 figures 

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Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI


Jun 22, 2022
Q. Vera Liao, Yunfeng Zhang, Ronny Luss, Finale Doshi-Velez, Amit Dhurandhar

* draft 

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Local Explanations for Reinforcement Learning


Feb 08, 2022
Ronny Luss, Amit Dhurandhar, Miao Liu


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Auto-Transfer: Learning to Route Transferrable Representations


Feb 04, 2022
Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar

* Accepted for publication in ICLR 2022 

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Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners


Feb 02, 2022
Karthikeyan Natesan Ramamurthy, Amit Dhurandhar, Dennis Wei, Zaid Bin Tariq


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Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning


Jan 28, 2022
Amit Dhurandhar, Karthikeyan Ramamurthy, Kartik Ahuja, Vijay Arya


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