Keywords
Affiliated Institutions
Related Publications
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...
Interior Methods for Nonlinear Optimization
Interior methods are an omnipresent, conspicuous feature of the constrained optimization landscape today, but it was not always so. Primarily in the form of barrier methods, int...
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...
Interior-Point Method for Nuclear Norm Approximation with Application to System Identification
The nuclear norm (sum of singular values) of a matrix is often used in convex heuristics for rank minimization problems in control, signal processing, and statistics. Such heuri...
Determinant Maximization with Linear Matrix Inequality Constraints
The problem of maximizing the determinant of a matrix subject to linear matrix inequalities (LMIs) arises in many fields, including computational geometry, statistics, system id...
Publication Info
- Year
- 2004
- Type
- article
- Volume
- 53
- Issue
- 1
- Pages
- 65-78
- Citations
- 2713
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1016/j.sysconle.2004.02.022