Ronny Luss  Ronny Luss photo         

contact information

Research Scientist
Thomas J. Watson Research Center, Yorktown Heights, NY USA



AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
Journal of Machine Learning Research21, 2020

Enhancing Simple Models by Exploiting What They Already Know
Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss
ICML 2020: 37th International Conference on Machine Learning, pp. 2525-2534
Abstract   interpretability, decision tree, artificial neural network, random forest, weighting, small data, machine learning, sample, computer science, simple, artificial intelligence


Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
A. Choromanska, B. Cowen, S. Kumaravel, R. Luss, M. Rigotti, I. Rish, P. Diachille, V. Gurev, B. Kingsbury, R. Tejwani, D. Bouneffouf
International Conference on Machine Learning, pp. 1193-1202, 2019


Improving Simple Models with Confidence Profiles
Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder A. Olsen
NeurIPS, 2018

Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives
Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Paishun Ting, Karthikeyan Shanmugam, Payel Das
NeurIPS, 2018


Bounded Isotonic Regression
Ronny Luss, Saharon Rosset
Electronic Journal of Statistics 11(2), 4488-4514, 2017


Temporal Causal Modeling
A. Kambadur, A. Lozano, and R. Luss
Financial Signal Processing and Machine Learning, 41--66, Wiley Online Library, 2016

Interpretable policies for dynamic product recommendations
Petrik, Marek and Luss, Ronny
Proc. Conf. Uncertainty Artif. Intell, pp. 74, 2016


Predicting abnormal returns from news using text classification
Ronny Luss, Alexandre d'Aspremont
Quantitative Finance 15(6), 999-1012, Taylor \& Francis, 2015
Published online 2012


Social media and customer behavior analytics for personalized customer engagements
S. Buckley, M. Ettl, P. Jain, R. Luss, M. Petrik, R. K. Ravi, and C. Venkatramani
IBM Journal of Research and Development 58(5/6), 7--1, IBM, 2014

Orthogonal matching pursuit for sparse quantile regression
Aravkin, Aleksandr and Lozano, Aurelie and Luss, Ronny and Kambadur, Prabhajan
Data Mining (ICDM), 2014 IEEE International Conference on, pp. 11--19

Generalized Isotonic Regression
Ronny Luss, Saharon Rosset
Journal of Computational and Graphical Statistics 23(1), 192--210, Taylor \& Francis, 2014



Efficient regularized isotonic regression with application to gene--gene interaction search
Ronny Luss, Saharon Rosset, Moni Shahar, others
The Annals of Applied Statistics 6(1), 253--283, Institute of Mathematical Statistics, 2012


Convex approximations to sparse PCA via Lagrangian duality
Ronny Luss, Marc Teboulle
Operations Research Letters 39(1), 57--61, Elsevier, 2011


Decomposing isotonic regression for efficiently solving large problems
Ronny Luss, Saharon Rosset, Moni Shahar
Advances in Neural Information Processing Systems, pp. 1513--1521, 2010

Clustering and feature selection using sparse principal component analysis
Ronny Luss, Alexandre d’Aspremont
Optimization and Engineering 11(1), 145--157, Springer, 2010


Support Vector Machine Classification with Indefinite Kernels
R. Luss, A. d'Aspremont
Mathematical Programming Computation 1(2-3), Springer, 2009


Support vector machine classification with indefinite kernels
Ronny Luss, Alexandre d'Aspremont
Advances in Neural Information Processing Systems, pp. 953--960, 2008