468 citations · 768 across the 16 of their papers we have counts for
6 papers · 1 filter
A New Architecture for Optimization Modeling Frameworks
Matt Wytock, Steven Diamond, Felix Heide +1
We propose a new architecture for optimization modeling frameworks in which solvers are expressed as computation graphs in a framework like TensorFlow rather than as standalone pro…
Disciplined Multi-Convex Programming
Xinyue Shen, Steven Diamond, Madeleine Udell +2
A multi-convex optimization problem is one in which the variables can be partitioned into sets over which the problem is convex when the other variables are fixed. Multi-convex pro…
Disciplined Convex-Concave Programming
Xinyue Shen, Steven Diamond, Yuantao Gu +1
In this paper we introduce disciplined convex-concave programming (DCCP), which combines the ideas of disciplined convex programming (DCP) with convex-concave programming (CCP). Co…
CVXPY: A Python-Embedded Modeling Language for Convex Optimization
Steven Diamond, Stephen Boyd
CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math…
Stochastic Matrix-Free Equilibration
Steven Diamond, Stephen Boyd
We present a novel method for approximately equilibrating a matrix using only multiplication by and . Our method is based on convex optimizati…
A General System for Heuristic Solution of Convex Problems over Nonconvex Sets
Steven Diamond, Reza Takapoui, Stephen Boyd
We describe general heuristics to approximately solve a wide variety of problems with convex objective and decision variables from a nonconvex set. The heuristics, which employ con…