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CVPR
2010
IEEE
13 years 11 months ago
Classification and Clustering via Dictionary Learning with Structured Incoherence
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
UM
2009
Springer
14 years 2 months ago
Predicting Customer Models Using Behavior-Based Features in Shops
Abstract. Recent sensor technologies have enabled the capture of users’ behavior data. Given the large amount of data currently available from sensor-equipped environments, it is...
Junichiro Mori, Yutaka Matsuo, Hitoshi Koshiba, Ke...
PPSN
2010
Springer
13 years 6 months ago
Feature Selection for Multi-purpose Predictive Models: A Many-Objective Task
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
Alan P. Reynolds, David W. Corne, Michael J. Chant...
JSW
2007
126views more  JSW 2007»
13 years 8 months ago
On Remote and Virtual Experiments in eLearning
— The science of physics is based on theories and models as well as experiments: the former structure relations and simplify reality to a degree such that predictions on physical...
Sabina Jeschke, Harald Scheel, Thomas Richter, Chr...
MLMI
2007
Springer
14 years 2 months ago
Using Prosodic Features in Language Models for Meetings
Abstract. Prosody has been actively studied as an important knowledge source for speech recognition and understanding. In this paper, we are concerned with the question of exploiti...
Songfang Huang, Steve Renals