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ECCV
2010
Springer
15 years 8 months ago
Convolutional learning of spatio-temporal features
Abstract. We address the problem of learning good features for understanding video data. We introduce a model that learns latent representations of image sequences from pairs of su...
CVPR
2012
IEEE
13 years 8 months ago
Stream-based Joint Exploration-Exploitation Active Learning
Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
CEC
2010
IEEE
15 years 4 months ago
Learning-assisted evolutionary search for scalable function optimization: LEM(ID3)
Inspired originally by the Learnable Evolution Model(LEM) [5], we investigate LEM(ID3), a hybrid of evolutionary search with ID3 decision tree learning. LEM(ID3) involves interleav...
Guleng Sheri, David Corne
CORR
2010
Springer
152views Education» more  CORR 2010»
15 years 3 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
COLT
2004
Springer
15 years 8 months ago
Regularization and Semi-supervised Learning on Large Graphs
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
Mikhail Belkin, Irina Matveeva, Partha Niyogi