ALIFE
2002
13 years 11 months ago
2002
In this paper, we study the relationship between the two techniques known as ant colony optimization (aco) and stochastic gradient descent. More precisely, we show that some empir...
JMLR
2006
13 years 11 months ago
2006
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
JMLR
2008
13 years 11 months ago
2008
A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...
ICANN
2001
Springer
14 years 4 months ago
2001
Springer
The method of conjugate gradients provides a very effective way to optimize large, deterministic systems by gradient descent. In its standard form, however, it is not amenable to ...
ICC
2007
IEEE
14 years 5 months ago
2007
IEEE
—We present a new algorithm for vertical handover and dynamic network selection, based on a combination of multiattribute utility theory, kernel learning and stochastic gradient ...
ICML
2008
IEEE
15 years 10 days ago
2008
IEEE
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
ICML
2007
IEEE
15 years 10 days ago
2007
IEEE
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 stocha...
ICIP
2005
IEEE
15 years 1 months ago
2005
IEEE
This paper introduces a new registration method estimating the displacement field of bodies which deformations are constrained by an articulated rigid body. We propose an articula...