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Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in…
Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
This work aims to show using novel theoretical analysis, algorithms, and implementation that SGD can be implemented without any locking, and presents an update scheme called HOGWILD! which allows processors access to shared memory with the possibility of overwriting each other's work.
Numerical Optimization (Springer Series in Operations Research and Financial Engineering)
Numerical optimization presents a graduate text, in continuous presents, that talks extensively about algorithmic performance and thinking, and about mathematical optimization in understanding of initiative.
Primal-Dual Interior-Point Methods
- Stephen J. Wright
- Computer ScienceOther Titles in Applied Mathematics
- 1 January 1997
This chapter discusses Primal Method Primal-Dual Methods, Path-Following Algorithm, and Infeasible-Interior-Point Algorithms, and their applications to Linear Programming and Interior-Point Methods.
Sparse Reconstruction by Separable Approximation
- Stephen J. Wright, R. Nowak, Mário A. T. Figueiredo
- Computer Science, MathematicsIEEE Transactions on Signal Processing
- 12 May 2008
This work proposes iterative methods in which each step is obtained by solving an optimization subproblem involving a quadratic term with diagonal Hessian plus the original sparsity-inducing regularizer, and proves convergence of the proposed iterative algorithm to a minimum of the objective function.
Coordinate descent algorithms
- Stephen J. Wright
- Computer ScienceMath. Program.
- 17 February 2015
A certain problem structure that arises frequently in machine learning applications is shown, showing that efficient implementations of accelerated coordinate descent algorithms are possible for problems of this type.
Computational Methods for Sparse Solution of Linear Inverse Problems
This paper surveys the major practical algorithms for sparse approximation with specific attention to computational issues, to the circumstances in which individual methods tend to perform well, and to the theoretical guarantees available.
Power Awareness in Network Design and Routing
- Joseph Chabarek, J. Sommers, P. Barford, C. Estan, David Tsiang, Stephen J. Wright
- Computer ScienceIEEE INFOCOM - The 27th Conference on Computer…
- 13 April 2008
This paper describes the power and associated heat management challenges in today's routers and advocates a broad approach to addressing this problem that includes making power-awareness a primary objective in the design and configuration of networks, and in theDesign and implementation of network protocols.
Application of Interior-Point Methods to Model Predictive Control
We present a structured interior-point method for the efficient solution of the optimal control problem in model predictive control. The cost of this approach is linear in the horizon length,…
Distributed MPC Strategies With Application to Power System Automatic Generation Control
- Aswin N. Venkat, I. Hiskens, J. Rawlings, Stephen J. Wright
- Mathematics, EngineeringIEEE Transactions on Control Systems Technology
- 25 April 2008
A distributed model predictive control framework, suitable for controlling large-scale networked systems such as power systems, is presented and the distributed MPC algorithm is feasible and closed-loop stable under intermediate termination.