8 citations · 17 across the 4 of their papers we have counts for
4 papers
Efficient Domain Adaptation of Multimodal Embeddings using Constrastive Learning
Georgios Margaritis, Periklis Petridis, Dimitris J. Bertsimas
Recent advancements in machine learning (ML), natural language processing (NLP), and foundational models have shown promise for real-life applications in critical, albeit compute-c…
Adaptive Optimization for Prediction with Missing Data
Dimitris Bertsimas, Arthur Delarue, Jean Pauphilet
When training predictive models on data with missing entries, the most widely used and versatile approach is a pipeline technique where we first impute missing entries and then com…
A Stochastic Benders Decomposition Scheme for Large-Scale Stochastic Network Design
Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet +1
Network design problems involve constructing edges in a transportation or supply chain network to minimize construction and daily operational costs. We study a stochastic version w…
Simple Imputation Rules for Prediction with Missing Data: Contrasting Theoretical Guarantees with Empirical Performance
Dimitris Bertsimas, Arthur Delarue, Jean Pauphilet
Missing data is a common issue in real-world datasets. This paper studies the performance of impute-then-regress pipelines by contrasting theoretical and empirical evidence. We est…