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ICML
2005
IEEE
14 years 8 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
ICMCS
2006
IEEE
131views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Self-Supervised Learning for Robust Video Indexing
The performance of video analysis and indexing algorithms strongly depends on the type, content and recording characteristics of the analyzed video. Current video indexing approac...
Ralph Ewerth, Bernd Freisleben
AUSDM
2006
Springer
177views Data Mining» more  AUSDM 2006»
13 years 11 months ago
On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
Tatjana Eitrich, Bruno Lang
NIPS
2001
13 years 9 months ago
Adaptive Sparseness Using Jeffreys Prior
In this paper we introduce a new sparseness inducing prior which does not involve any (hyper)parameters that need to be adjusted or estimated. Although other applications are poss...
Mário A. T. Figueiredo
ITS
2010
Springer
115views Multimedia» more  ITS 2010»
14 years 10 days ago
In the Zone: Towards Detecting Student Zoning Out Using Supervised Machine Learning
This paper explores automatically detecting student zoning out while performing a spoken learning task. Standard supervised machine learning techniques were used to create classiï¬...
Joanna Drummond, Diane J. Litman