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EACL
2006
ACL Anthology
13 years 11 months ago
Improving Probabilistic Latent Semantic Analysis with Principal Component Analysis
Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, th...
Ayman Farahat, Francine Chen
UIST
2006
ACM
14 years 3 months ago
Viz: a visual analysis suite for explaining local search behavior
NP-hard combinatorial optimization problems are common in real life. Due to their intractability, local search algorithms are often used to solve such problems. Since these algori...
Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
JMLR
2006
99views more  JMLR 2006»
13 years 9 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
PODS
2008
ACM
153views Database» more  PODS 2008»
14 years 9 months ago
Approximation algorithms for co-clustering
Co-clustering is the simultaneous partitioning of the rows and columns of a matrix such that the blocks induced by the row/column partitions are good clusters. Motivated by severa...
Aris Anagnostopoulos, Anirban Dasgupta, Ravi Kumar
ICPR
2006
IEEE
14 years 10 months ago
Non-Iterative Two-Dimensional Linear Discriminant Analysis
Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled data in a vector space. Recently, LDA has been extended to...
Kohei Inoue, Kiichi Urahama