146 search results - page 4 / 30 » Online Gradient Descent Learning Algorithms |
111
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ICASSP
2009
IEEE
15 years 8 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
16 years 2 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 ...
154
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JMLR
2008
15 years 1 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...
121
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ICML
2008
IEEE
16 years 2 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...
121
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COLT
2006
Springer
15 years 5 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...