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» On the Convergence of Bound Optimization Algorithms
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NIPS
2007
13 years 11 months ago
Boosting Algorithms for Maximizing the Soft Margin
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...
ICCV
2003
IEEE
14 years 12 months ago
Globally Convergent Autocalibration
Existing autocalibration techniques use numerical optimization algorithms that are prone to the problem of local minima. To address this problem, we have developed a method where ...
Arrigo Benedetti, Alessandro Busti, Michela Farenz...
FOCM
2006
50views more  FOCM 2006»
13 years 10 months ago
Online Learning Algorithms
In this paper, we study an online learning algorithm in Reproducing Kernel Hilbert Spaces (RKHS) and general Hilbert spaces. We present a general form of the stochastic gradient m...
Steve Smale, Yuan Yao
ICIP
1999
IEEE
14 years 11 months ago
Efficient Approximation of Gray-Scale Images Through Bounded Error Triangular Meshes
This paper presents an iterative algorithm for approximating gray-scale images with adaptive triangular meshes ensuring a given tolerance. At each iteration, the algorithm applies...
Angel Domingo Sappa, Boris Xavier Vintimilla, Migu...
FOCI
2007
IEEE
14 years 1 months ago
Evolutionary Algorithms in the Presence of Noise: To Sample or Not to Sample
Abstract-- In this paper, we empirically analyze the convergence behavior of evolutionary algorithms (evolution strategies
Hans-Georg Beyer, Bernhard Sendhoff