129 citations · 365 across the 13 of their papers we have counts for
13 papers
A Statistical Interpretation of the Maximum Subarray Problem
Dennis Wei, Dmitry M. Malioutov
Maximum subarray is a classical problem in computer science that given an array of numbers aims to find a contiguous subarray with the largest sum. We focus on its use for a noisy…
Efficient Learning of Interpretable Classification Rules
Bishwamittra Ghosh, Dmitry Malioutov, Kuldeep S. Meel
Machine learning has become omnipresent with applications in various safety-critical domains such as medical, law, and transportation. In these domains, high-stake decisions provid…
MLIC: A MaxSAT-Based framework for learning interpretable classification rules
Dmitry Malioutov, Kuldeep S. Meel
The wide adoption of machine learning approaches in the industry, government, medicine and science has renewed the interest in interpretable machine learning: many decisions are to…
Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017)
Been Kim, Dmitry M. Malioutov, Kush R. Varshney +1
This is the Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017), which was held in Sydney, Australia, August 10, 2017. Invited speakers w…
Proceedings of the 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016)
Been Kim, Dmitry M. Malioutov, Kush R. Varshney
This is the Proceedings of the 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016), which was held in New York, NY, June 23, 2016. Invited speakers were Sus…
Interpretable Two-level Boolean Rule Learning for Classification
Guolong Su, Dennis Wei, Kush R. Varshney +1
As a contribution to interpretable machine learning research, we develop a novel optimization framework for learning accurate and sparse two-level Boolean rules. We consider rules…