activity
20132019
most citedSupersparse Linear Integer Models for Interpretable Classification

27 citations · 40 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ML2019★ 3 cited

Reducing Exploration of Dying Arms in Mortal Bandits

Stefano Tracà, Cynthia Rudin, Weiyu Yan

Mortal bandits have proven to be extremely useful for providing news article recommendations, running automated online advertising campaigns, and for other applications where the s…

math.AP2015

On the Cauchy problem for non-local Ornstein--Uhlenbeck operators

Enrico Priola, Stefano Tracà

We study the Cauchy problem involving non-local Ornstein-Uhlenbeck operators in finite and infinite dimensions. We prove classical solvability without requiring that the Lévy measu…

stat.ML2015★ 2 cited

Regulating Greed Over Time in Multi-Armed Bandits

Stefano Tracà, Cynthia Rudin, Weiyu Yan

In retail, there are predictable yet dramatic time-dependent patterns in customer behavior, such as periodic changes in the number of visitors, or increases in customers just befor…

stat.ML2013★ 8 cited

Supersparse Linear Integer Models for Predictive Scoring Systems

Berk Ustun, Stefano Traca, Cynthia Rudin

We introduce Supersparse Linear Integer Models (SLIM) as a tool to create scoring systems for binary classification. We derive theoretical bounds on the true risk of SLIM scoring s…

stat.ML2013★ 27 cited

Supersparse Linear Integer Models for Interpretable Classification

Berk Ustun, Stefano Tracà, Cynthia Rudin

Scoring systems are classification models that only require users to add, subtract and multiply a few meaningful numbers to make a prediction. These models are often used because t…