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One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

Sep 14, 2019
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang


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Leveraging Simple Model Predictions for Enhancing its Performance

May 30, 2019
Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss


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Generating Contrastive Explanations with Monotonic Attribute Functions

May 29, 2019
Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Karthikeyan Shanmugam, Chun-Chen Tu


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Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives

Oct 29, 2018
Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Paishun Ting, Karthikeyan Shanmugam, Payel Das


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TIP: Typifying the Interpretability of Procedures

Oct 29, 2018
Amit Dhurandhar, Vijay Iyengar, Ronny Luss, Karthikeyan Shanmugam


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Beyond Backprop: Online Alternating Minimization with Auxiliary Variables

Oct 24, 2018
Anna Choromanska, Sadhana Kumaravel, Ronny Luss, Irina Rish, Brian Kingsbury, Mattia Rigotti, Paolo DiAchille, Viatcheslav Gurev, Ravi Tejwani, Djallel Bouneffouf

* First four authors contributed equally to this work: A.C. - theory, manuscript, S.K. - code, experiments, R.L. - algorithm, experiments, I.R. - algorithm, manuscript 

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Stochastic Gradient Descent with Biased but Consistent Gradient Estimators

Jul 31, 2018
Jie Chen, Ronny Luss


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Improving Simple Models with Confidence Profiles

Jul 19, 2018
Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder Olsen

* 16 pages 

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A Formal Framework to Characterize Interpretability of Procedures

Jul 12, 2017
Amit Dhurandhar, Vijay Iyengar, Ronny Luss, Karthikeyan Shanmugam

* presented at 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017), Sydney, NSW, Australia 

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Sparse Quantile Huber Regression for Efficient and Robust Estimation

Feb 19, 2014
Aleksandr Y. Aravkin, Anju Kambadur, Aurelie C. Lozano, Ronny Luss

* 9 pages 

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Support Vector Machine Classification with Indefinite Kernels

Aug 04, 2009
Ronny Luss, Alexandre d'Aspremont

* Final journal version. A few typos fixed 

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Predicting Abnormal Returns From News Using Text Classification

Jun 24, 2009
Ronny Luss, Alexandre d'Aspremont

* Larger data sets, results on time of day effect, and use of delta hedged covered call options to trade on daily predictions 

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Clustering and Feature Selection using Sparse Principal Component Analysis

Oct 08, 2008
Ronny Luss, Alexandre d'Aspremont

* More experiments 

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