146 search results - page 4 / 30 » Online Gradient Descent Learning Algorithms |
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
In this paper, we propose a distributed learning strategy in wireless sensor networks. Taking advantage of recent developments on kernel-based machine learning, we consider a new ...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
We present an algorithm for finding an ssparse vector x that minimizes the squareerror y - x 2 where satisfies the restricted isometry property (RIP), with isometric constant 2s ...
JMLR
2008
13 years 7 months ago
2008
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
ICML
2008
IEEE
14 years 8 months 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...
COLT
2006
Springer
13 years 11 months ago
2006
Springer
In an online convex optimization problem a decision-maker makes a sequence of decisions, i.e., chooses a sequence of points in Euclidean space, from a fixed feasible set. After ea...