activity
20062022
most citedThe Price of Interpretability

30 citations · 101 across the 13 of their papers we have counts for

collaborators
Showing 2018Show all

6 papers · 1 filter

stat.ML2018

Interpretable Clustering via Optimal Trees

Dimitris Bertsimas, Agni Orfanoudaki, Holly Wiberg

State-of-the-art clustering algorithms use heuristics to partition the feature space and provide little insight into the rationale for cluster membership, limiting their interpreta…

stat.ML2018

Imputation of Clinical Covariates in Time Series

Dimitris Bertsimas, Agni Orfanoudaki, Colin Pawlowski

Missing data is a common problem in real-world settings and particularly relevant in healthcare applications where researchers use Electronic Health Records (EHR) and results of ob…

math.OC2018

The Voice of Optimization

Dimitris Bertsimas, Bartolomeo Stellato

We introduce the idea that using optimal classification trees (OCTs) and optimal classification trees with-hyperplanes (OCT-Hs), interpretable machine learning algorithms developed…

math.OC2018

Interpretable Matrix Completion: A Discrete Optimization Approach

Dimitris Bertsimas, Michael Lingzhi Li

We consider the problem of matrix completion on an matrix. We introduce the problem of Interpretable Matrix Completion that aims to provide meaningful insights for the…

math.OC2018

A Scalable Algorithm for Two-Stage Adaptive Linear Optimization

Dimitris Bertsimas, Shimrit Shtern

The column-and-constraint generation (CCG) method was introduced by \citet{Zeng2013} for solving two-stage adaptive optimization. We found that the CCG method is quite scalable, bu…

stat.ML2018

Optimization over Continuous and Multi-dimensional Decisions with Observational Data

Dimitris Bertsimas, Christopher McCord

We consider the optimization of an uncertain objective over continuous and multi-dimensional decision spaces in problems in which we are only provided with observational data. We p…