53 citations · 292 across the 29 of their papers we have counts for
6 papers · 1 filter
A geometric way to build strong mixed-integer programming formulations
Joey Huchette, Juan Pablo Vielma
We give an explicit geometric way to build mixed-integer programming (MIP) formulations for unions of polyhedra. The construction is simply described in terms of spanning hyperplan…
Strong mixed-integer programming formulations for trained neural networks
Ross Anderson, Joey Huchette, Christian Tjandraatmadja +1
We present an ideal mixed-integer programming (MIP) formulation for a rectified linear unit (ReLU) appearing in a trained neural network. Our formulation requires a single binary v…
Strong mixed-integer programming formulations for trained neural networks
Ross Anderson, Joey Huchette, Will Ma +2
We present strong mixed-integer programming (MIP) formulations for high-dimensional piecewise linear functions that correspond to trained neural networks. These formulations can be…
Dynamic Automatic Differentiation of GPU Broadcast Kernels
Jarrett Revels, Tim Besard, Valentin Churavy +2
We show how forward-mode automatic differentiation (AD) can be employed within larger reverse-mode computations to dynamically differentiate broadcast operations in a GPU-friendly…
Building Representative Matched Samples with Multi-valued Treatments in Large Observational Studies
Magdalena Bennett, Juan Pablo Vielma, Jose R. Zubizarreta
In this paper, we present a new way of matching in observational studies that overcomes three limitations of existing matching approaches. First, it directly balances covariates wi…
Outer Approximation With Conic Certificates For Mixed-Integer Convex Problems
Chris Coey, Miles Lubin, Juan Pablo Vielma
A mixed-integer convex (MI-convex) optimization problem is one that becomes convex when all integrality constraints are relaxed. We present a branch-and-bound LP outer approximatio…