30 citations · 122 across the 17 of their papers we have counts for
11 papers · 1 filter
Adaptive Pricing in Unit Commitment Under Load and Capacity Uncertainty
Dimitris Bertsimas, Angelos G. Koulouras
The increase of renewables in the grid and the volatility of the load create uncertainties in the day-ahead prices of electricity markets. Adaptive robust optimization (ARO) and st…
A Machine Learning Approach to Two-Stage Adaptive Robust Optimization
Dimitris Bertsimas, Cheol Woo Kim
We propose an approach based on machine learning to solve two-stage linear adaptive robust optimization (ARO) problems with binary here-and-now variables and polyhedral uncertainty…
Optimal Control of Multiclass Fluid Queueing Networks: A Machine Learning Approach
Dimitris Bertsimas, Cheol Woo Kim
We propose a machine learning approach to the optimal control of multiclass fluid queueing networks (MFQNETs) that provides explicit and insightful control policies. We prove that…
Finding Neurons in a Haystack: Case Studies with Sparse Probing
Wes Gurnee, Neel Nanda, Matthew Pauly +3
Despite rapid adoption and deployment of large language models (LLMs), the internal computations of these models remain opaque and poorly understood. In this work, we seek to under…
Compressed Sensing: A Discrete Optimization Approach
Dimitris Bertsimas, Nicholas A. G. Johnson
We study the Compressed Sensing (CS) problem, which is the problem of finding the most sparse vector that satisfies a set of linear measurements up to some numerical tolerance. We…
Improving Stability in Decision Tree Models
Dimitris Bertsimas, Vassilis Digalakis
Owing to their inherently interpretable structure, decision trees are commonly used in applications where interpretability is essential. Recent work has focused on improving variou…