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» Approximating the 2-Interval Pattern Problem
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ICML
2004
IEEE
14 years 10 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
APPT
2005
Springer
14 years 3 months ago
Principal Component Analysis for Distributed Data Sets with Updating
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
Zheng-Jian Bai, Raymond H. Chan, Franklin T. Luk
CORR
2007
Springer
110views Education» more  CORR 2007»
13 years 9 months ago
Information-theoretic limits on sparsity recovery in the high-dimensional and noisy setting
The problem of recovering the sparsity pattern of a fixed but unknown vector β∗ ∈ Rp based on a set of n noisy observations arises in a variety of settings, including subset...
Martin J. Wainwright
KDD
2005
ACM
166views Data Mining» more  KDD 2005»
14 years 10 months ago
A general model for clustering binary data
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Tao Li
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
14 years 3 months ago
Nonlinear feature extraction using a neuro genetic hybrid
Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure o...
Yung-Keun Kwon, Byung Ro Moon