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» Kernels for Global Constraints
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AAAI
2010
13 years 10 months ago
Smooth Optimization for Effective Multiple Kernel Learning
Multiple Kernel Learning (MKL) can be formulated as a convex-concave minmax optimization problem, whose saddle point corresponds to the optimal solution to MKL. Most MKL methods e...
Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu...
TSMC
2010
13 years 3 months ago
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Sheng Chen, Xia Hong, Chris J. Harris
ICASSP
2011
IEEE
13 years 24 days ago
Robust video object tracking based on multiple kernels with projected gradients
In kernel-based video object tracking, the use of single kernel often suffers from the occlusion. In order to provide more robust tracking performance, multiple inter-related kern...
Chun-Te Chu, Jenq-Neng Hwang, Hung-I. Pai, Kung-Mi...
CP
2008
Springer
13 years 11 months ago
A Soft Constraint of Equality: Complexity and Approximability
We introduce the SoftAllEqual global constraint, which maximizes the number of equalities holding between pairs of assignments to a set of variables. We study the computational com...
Emmanuel Hebrard, Barry O'Sullivan, Igor Razgon
CONSTRAINTS
2007
83views more  CONSTRAINTS 2007»
13 years 9 months ago
Generic Incremental Algorithms for Local Search
When a new (global) constraint is introduced in local search, measures for the penalty and variable conflicts of that constraint must be defined, and incremental algorithms for m...
Magnus Ågren, Pierre Flener, Justin Pearson