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SnapVX: A Network-Based Convex Optimization Solver.

David Hallac¹, Christopher Wong², Steven Diamond²

¹Department of Electrical Engineering, Stanford University, Stanford, CA, 94305.

Journal of Machine Learning Research : JMLR

|March 31, 2018

Summary

This summary is machine-generated.

SnapVX is a new solver for network convex optimization problems. It offers a fast, scalable, and globally convergent solution by integrating Snap.py and CVXPY for efficient large-scale graph processing and subproblem modeling.

Keywords:

ADMM convex optimization data mining graphs network analytics

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Area of Science:

Computational Mathematics
Computer Science
Operations Research

Background:

Convex optimization problems on networks are common in various scientific and engineering fields.
Existing solvers may lack scalability or guaranteed convergence for large-scale network problems.
Integrating graph processing and convex optimization modeling frameworks presents unique challenges.

Purpose of the Study:

To introduce SnapVX, a high-performance solver for convex optimization problems on networks.
To provide a scalable and globally convergent solution for large-scale network optimization.
To offer a user-friendly Python interface combining graph processing and convex optimization capabilities.

Main Methods:

SnapVX integrates Snap.py (large-scale graph processing) and CVXPY (convex optimization modeling).
The solver is based on the Alternating Direction Method of Multipliers (ADMM).
It is designed for efficient storage, analysis, parallelization, and solving of optimization problems.

Main Results:

SnapVX delivers a fast and scalable solution for network convex optimization.
Guaranteed global convergence is achieved for the targeted problem class.
The software provides a customizable yet easy-to-use Python interface.

Conclusions:

SnapVX offers an efficient and reliable tool for solving large-scale convex optimization problems on networks.
The integration of graph processing and convex optimization frameworks enhances problem-solving capabilities.
SnapVX is applicable to a variety of real-world applications requiring network optimization.