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FCT
2007
Springer
15 years 6 months ago
Product Rules in Semidefinite Programming
Abstract. In recent years we have witnessed the proliferation of semidefinite programming bounds in combinatorial optimization [1,5,8], quantum computing [9,2,3,6,4,16] and even in...
Rajat Mittal, Mario Szegedy
138
Voted
ACML
2009
Springer
15 years 6 months ago
Max-margin Multiple-Instance Learning via Semidefinite Programming
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
Yuhong Guo
84
Voted
KDD
2003
ACM
97views Data Mining» more  KDD 2003»
16 years 2 months ago
Reducing large diagonals in kernel matrices through semidefinite programming
Hsiao-Mei Lu, Sumeet Gupta, Yang Dai
166
Voted
ICML
2005
IEEE
16 years 3 months ago
Analysis and extension of spectral methods for nonlinear dimensionality reduction
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
Fei Sha, Lawrence K. Saul
214
Voted

Book
518views
17 years 21 days ago
Convex Optimization
Book web site includes links to a full course, software, and other material.
Stephen Boyd, Lieven Vandenberghe