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» Machine Learning by Function Decomposition
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ICML
2003
IEEE
16 years 2 months ago
Margin Distribution and Learning
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Ashutosh Garg, Dan Roth
ICML
2004
IEEE
15 years 7 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
ICML
2006
IEEE
16 years 2 months ago
Experience-efficient learning in associative bandit problems
We formalize the associative bandit problem framework introduced by Kaelbling as a learning-theory problem. The learning environment is modeled as a k-armed bandit where arm payof...
Alexander L. Strehl, Chris Mesterharm, Michael L. ...
CONIELECOMP
2006
IEEE
15 years 7 months ago
Chaotic Time Series Approximation Using Iterative Wavelet-Networks
This paper presents a wavelet neural-network for learning and approximation of chaotic time series. Wavelet-networks are inspired by both feed-forward neural networks and the theo...
E. S. Garcia-Trevino, Vicente Alarcón Aquin...
CORR
2002
Springer
82views Education» more  CORR 2002»
15 years 1 months ago
Using eigenvectors of the bigram graph to infer morpheme identity
This paper describes the results of some experiments exploring statistical methods to infer syntactic categories from a raw corpus in an unsupervised fashion. It shares certain po...
Mikhail Belkin, John A. Goldsmith