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» Spectral Algorithms for Supervised Learning
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ESANN
2006
14 years 11 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
14 years 11 months ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
TASLP
2010
134views more  TASLP 2010»
14 years 4 months ago
Multiple Fundamental Frequency Estimation by Modeling Spectral Peaks and Non-Peak Regions
This paper presents a maximum likelihood approach to multiple fundamental frequency (F0) estimation for a mixture of harmonic sound sources, where the power spectrum of a time fra...
Zhiyao Duan, Bryan Pardo, Changshui Zhang
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
15 years 10 months ago
A parallel learning algorithm for text classification
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify te...
Canasai Kruengkrai, Chuleerat Jaruskulchai
ICML
2004
IEEE
15 years 10 months ago
Online and batch learning of pseudo-metrics
We describe and analyze an online algorithm for supervised learning of pseudo-metrics. The algorithm receives pairs of instances and predicts their similarity according to a pseud...
Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng