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NIPS
2001
13 years 10 months ago
Grammatical Bigrams
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...
Mark A. Paskin
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
ESWA
2011
220views Database» more  ESWA 2011»
13 years 13 days ago
Unsupervised neural models for country and political risk analysis
This interdisciplinary research project focuses on relevant applications of Knowledge Discovery and Artificial Neural Networks in order to identify and analyse levels of country, b...
Álvaro Herrero, Emilio Corchado, Alfredo Ji...
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 9 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
CLEF
2007
Springer
14 years 3 months ago
Unsupervised Acquiring of Morphological Paradigms from Tokenized Text
This paper describes a rather simplistic method of unsupervised morphological analysis of words in an unknown language. All what is needed is a raw text corpus in the given langua...
Daniel Zeman