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» Spectral Algorithms for Supervised Learning
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SAC
2006
ACM
14 years 9 months ago
Combining supervised and unsupervised monitoring for fault detection in distributed computing systems
Fast and accurate fault detection is becoming an essential component of management software for mission critical systems. A good fault detector makes possible to initiate repair a...
Haifeng Chen, Guofei Jiang, Cristian Ungureanu, Ke...
PAMI
2012
13 years 5 days ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce
COLT
2005
Springer
15 years 3 months ago
Analysis of Perceptron-Based Active Learning
We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Montele...
ICDAR
1999
IEEE
15 years 2 months ago
Cursive Character Detection using Incremental Learning
This paper describes a new hybrid architecture for an artificial neural network classifier that enables incremental learning. The learning algorithm of the proposed architecture d...
Jean-François Hébert, Marc Parizeau,...
ICML
2009
IEEE
15 years 10 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou