# Stephen P. Boyd

Stanford

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- Publications
- Influence

Convex Optimization

- Stephen P. Boyd, L. Vandenberghe
- Computer Science, Mathematics
- IEEE Transactions on Automatic Control
- 1 March 2004

Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great… Expand

Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

- Stephen P. Boyd, Neal Parikh, E. Chu, Borja Peleato, Jonathan Eckstein
- Computer Science
- Found. Trends Mach. Learn.
- 23 May 2011

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is… Expand

Linear Matrix Inequalities in Systems and Control Theory

- Stephen P. Boyd
- Computer Science
- 1994

- 12,858
- 471

Enhancing Sparsity by Reweighted ℓ1 Minimization

- E. Candès, M. Wakin, Stephen P. Boyd
- Mathematics
- 10 November 2007

It is now well understood that (1) it is possible to reconstruct sparse signals exactly from what appear to be highly incomplete sets of linear measurements and (2) that this can be done by… Expand

Randomized gossip algorithms

- Stephen P. Boyd, Arpita Ghosh, B. Prabhakar, D. Shah
- Computer Science
- IEEE Transactions on Information Theory
- 1 June 2006

Motivated by applications to sensor, peer-to-peer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an… Expand

Proximal Algorithms

- Neal Parikh, Stephen P. Boyd
- Computer Science
- Found. Trends Optim.
- 27 November 2013

This monograph is about a class of optimization algorithms called proximal algorithms. Much like Newton's method is a standard tool for solving unconstrained smooth optimization problems of modest… Expand

Semidefinite Programming

- L. Vandenberghe, Stephen P. Boyd
- Computer Science
- SIAM Rev.
- 1 March 1996

In semidefinite programming, one minimizes a linear function subject to the constraint that an affine combination of symmetric matrices is positive semidefinite. Such a constraint is nonlinear and… Expand

Applications of second-order cone programming

- M. Lobo, L. Vandenberghe, Stephen P. Boyd, Hervé Lebret
- Mathematics
- 15 November 1998

In a second-Order cone program (SOCP) a linear function is minimized over the intersection of an affine set and the product of second-Order (quadratic) cones. SOCPs are nonlinear convex Problems that… Expand

Graph Implementations for Nonsmooth Convex Programs

- M. Grant, Stephen P. Boyd
- Mathematics, Computer Science
- Recent Advances in Learning and Control
- 2008

We describe graph implementations, a generic method for representing a convex function via its epigraph, described in a disciplined convex programming framework. This simple and natural idea allows a… Expand

A tutorial on geometric programming

- Stephen P. Boyd, Seung-Jean Kim, L. Vandenberghe, A. Hassibi
- Mathematics
- 10 April 2007

Abstract
A geometric program (GP) is a type of mathematical optimization problem characterized by objective and constraint functions that have a special form. Recently developed solution methods can… Expand