3 papers
math.OC2022
Sparse Convex Optimization Toolkit: A Mixed-Integer Framework
Alireza Olama, Eduardo Camponogara, Jan Kronqvist
This paper proposes an open-source distributed solver for solving Sparse Convex Optimization (SCO) problems over computational networks. Motivated by past algorithmic advances in m…
math.OC2021
Partition-based formulations for mixed-integer optimization of trained ReLU neural networks
Calvin Tsay, Jan Kronqvist, Alexander Thebelt +1
This paper introduces a class of mixed-integer formulations for trained ReLU neural networks. The approach balances model size and tightness by partitioning node inputs into a numb…
math.OC2021
Between steps: Intermediate relaxations between big-M and convex hull formulations
Jan Kronqvist, Ruth Misener, Calvin Tsay
This work develops a class of relaxations in between the big-M and convex hull formulations of disjunctions, drawing advantages from both. The proposed "P-split" formulations split…