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ICPR
2006
IEEE
14 years 10 months ago
A Semi-supervised SVM for Manifold Learning
Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
Zhili Wu, Chun-hung Li, Ji Zhu, Jian Huang
FOCI
2007
IEEE
14 years 3 months ago
Random Hypergraph Models of Learning and Memory in Biomolecular Networks: Shorter-Term Adaptability vs. Longer-Term Persistency
Recent progress in genomics and proteomics makes it possible to understand the biological networks at the systems level. We aim to develop computational models of learning and memo...
Byoung-Tak Zhang
CSL
2010
Springer
13 years 9 months ago
Active learning and semi-supervised learning for speech recognition: A unified framework using the global entropy reduction maxi
We propose a unified global entropy reduction maximization (GERM) framework for active learning and semi-supervised learning for speech recognition. Active learning aims to select...
Dong Yu, Balakrishnan Varadarajan, Li Deng, Alex A...
EDM
2009
286views Data Mining» more  EDM 2009»
13 years 6 months ago
Does Self-Discipline impact students' knowledge and learning?
In this study, we are interested to see the impact of self-discipline on students' knowledge and learning. Self-discipline can influence both learning rate as well as knowledg...
Yue Gong, Dovan Rai, Joseph Beck, Neil T. Hefferna...
IJAR
2010
130views more  IJAR 2010»
13 years 7 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki