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» Spectral Algorithms for Supervised Learning
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ACL
2006
14 years 11 months ago
Weakly Supervised Named Entity Transliteration and Discovery from Multilingual Comparable Corpora
Named Entity recognition (NER) is an important part of many natural language processing tasks. Current approaches often employ machine learning techniques and require supervised d...
Alexandre Klementiev, Dan Roth
ICML
2007
IEEE
15 years 10 months ago
Supervised feature selection via dependence estimation
We introduce a framework for filtering features that employs the Hilbert-Schmidt Independence Criterion (HSIC) as a measure of dependence between the features and the labels. The ...
Le Song, Alex J. Smola, Arthur Gretton, Karsten M....
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IJCNN
2006
IEEE
15 years 3 months ago
In-Place Learning for Positional and Scale Invariance
— In-place learning is a biologically inspired concept, meaning that the computational network is responsible for its own learning. With in-place learning, there is no need for a...
Juyang Weng, Hong Lu, Tianyu Luwang, Xiangyang Xue
ICML
2010
IEEE
14 years 10 months ago
Finding Planted Partitions in Nearly Linear Time using Arrested Spectral Clustering
We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high pro...
Nader H. Bshouty, Philip M. Long
TNN
2010
234views Management» more  TNN 2010»
14 years 4 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes