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» Unsupervised Learning Using MML
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PR
2006
120views more  PR 2006»
13 years 8 months ago
Alternative learning vector quantization
In this paper, we discuss the influence of feature vectors contributions at each learning time t on a sequential-type competitive learning algorithm. We then give a learning rate ...
Kuo-Lung Wu, Miin-Shen Yang
ACL
2011
13 years 11 days ago
Learning Word Vectors for Sentiment Analysis
Unsupervised vector-based approaches to semantics can model rich lexical meanings, but they largely fail to capture sentiment information that is central to many word meanings and...
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Da...
ICCV
2003
IEEE
14 years 10 months ago
Bayesian Clustering of Optical Flow Fields
We present a method for unsupervised learning of classes of motions in video. We project optical flow fields to a complete, orthogonal, a-priori set of basis functions in a probab...
Jesse Hoey, James J. Little
UAI
2008
13 years 10 months ago
Bayesian Out-Trees
A Bayesian treatment of latent directed graph structure for non-iid data is provided where each child datum is sampled with a directed conditional dependence on a single unknown p...
Tony Jebara
MVA
2010
130views Computer Vision» more  MVA 2010»
13 years 7 months ago
Neighborhood linear embedding for intrinsic structure discovery
In this paper, an unsupervised learning algorithm, neighborhood linear embedding (NLE), is proposed to discover the intrinsic structures such as neighborhood relationships, global ...
Shuzhi Sam Ge, Feng Guan, Yaozhang Pan, Ai Poh Loh