2016 Poster Sessions : A General System for Heuristic Solution of Nonconvex Problems

Student Name : Steven Diamond, Jaehyun Park, Reza Takapour
Advisor : Stephen Boyd
Research Areas: Information Systems
We describe general heuristics for certain classes of nonconvex problems. The heuristics, which employ convex relaxations, convex restrictions, local neighbor search methods, and the alternating direction method of multipliers (ADMM), require the solution of a modest number of convex problems, and are meant to apply to general problems, without much tuning. We also present NCVX, an extension package for CVXPY, for formulating and (approximately) solving these nonconvex problems in Python.

Steven Diamond is a PhD student in Computer Science at Stanford University, with research interests in convex optimization, domain specific languages for optimization, and matrix-free methods. He is the author of CVXPY, a widely used Python package for convex optimization.

Jaehyun Park is a PhD candidate in Computer Science at Stanford University. His research interests are convex optimization, combinatorial algorithms, and machine learning.

Reza Takapoui is a PhD student in Electrical Engineering at Stanford, with research interests in Convex Optimization, Machine Learning, and Statistics. Before joining Stanford, he studied Electrical Engineering and Mathematics and Computer Science at Sharif University of Technology. He has been awarded silver medal in International Mathematical Olympiad (IMO) 2007 and first prize in International Mathematica Competition for university students (IMC) 2010.