Keywords
Affiliated Institutions
Related Publications
Composite objective mirror descent
We present a new method for regularized convex optimization and analyze it under both online and stochastic optimization settings. In addition to unifying previously known first...
Interior-Point Polynomial Algorithms in Convex Programming
Written for specialists working in optimization, mathematical programming, or control theory. The general theory of path-following and potential reduction interior point polynom...
Pegasos
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stoc...
Conjugate-Gradient Methods for Large-Scale Nonlinear Optimization.
Abstract : In this paper we discuss several recent conjugate-gradient type methods for solving large-scale nonlinear optimization problems. We demonstrate how the performance of...
Variable metric methods of minimisation
Two basic approaches to the generation of conjugate directions are considered for the problem of unconstrained minimisation of quadratic functions. The first approach results in...
Publication Info
- Year
- 1987
- Type
- article
- Volume
- 39
- Issue
- 1
- Pages
- 93-116
- Citations
- 570
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1007/bf02592073