3 papers
math.OC2026
The Geometry of Linear Program Compression: An Exact Characterization and Learning Algorithm
Yuhan Ye, Omar Bennouna
We study how much a linear program (LP) can be compressed when solved repeatedly, given prior knowledge about its objective function. Existing data-driven projection methods learn…
math.OC2026
Parameterized Complexity of Stationarity Testing for Piecewise-Affine Functions and Shallow CNN Losses
Yuhan Ye
We study the parameterized complexity of testing approximate first-order stationarity at a prescribed point for continuous piecewise-affine (PA) functions, a basic task in nonsmoot…
math.OC2026
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…