6 papers · 1 filter
Learning Decision-Sufficient Representations for Linear Optimization
Yuhan Ye, Saurabh Amin, Asuman Ozdaglar
We study how to construct compressed datasets that suffice to recover optimal decisions in linear programs with an unknown cost vector lying in a prior set . Recen…
Data Informativeness in Linear Optimization under Uncertainty
Omar Bennouna, Amine Bennouna, Saurabh Amin +1
We study the problem of determining what data is required to solve a decision-making task when only partial information about the state of the world is available. Focusing on linea…
Reducing Contextual Stochastic Bilevel Optimization via Structured Function Approximation
Maxime Bouscary, Jiawei Zhang, Saurabh Amin
Contextual Stochastic Bilevel Optimization (CSBO) extends standard stochastic bilevel optimization (SBO) by incorporating context-dependent lower-level problems. CSBO problems are…
What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimization
Omar Bennouna, Amine Bennouna, Saurabh Amin +1
We study the fundamental question of how informative a dataset is for solving a given decision-making task. In our setting, the dataset provides partial information about unknown p…
Addressing misspecification in contextual optimization
Omar Bennouna, Jiawei Zhang, Saurabh Amin +1
We study a linear contextual optimization problem where a decision maker has access to historical data and contextual features to learn a cost prediction model aimed at minimizing…
Integrated Bundling and Pricing of Unique Items
Maxime Bouscary, Mazen Danaf, Saurabh Amin
Retailers have significant potential to improve recommendations through strategic bundling and pricing. By taking into account different types of customers and their purchasing dec…