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» Extremal Problems of Information Combining
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IDEAL
2000
Springer
15 years 9 months ago
Quantization of Continuous Input Variables for Binary Classification
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
Michal Skubacz, Jaakko Hollmén
ICDM
2009
IEEE
138views Data Mining» more  ICDM 2009»
15 years 3 months ago
Semantic-Rich Markov Models for Web Prefetching
Abstract--Domain knowledge for web applications is currently being made available as domain ontology with the advent of the semantic web, in which semantics govern relationships am...
Nizar R. Mabroukeh, Christie I. Ezeife
177
Voted
KAIS
2008
119views more  KAIS 2008»
15 years 6 months ago
An information-theoretic approach to quantitative association rule mining
Abstract. Quantitative Association Rule (QAR) mining has been recognized an influential research problem over the last decade due to the popularity of quantitative databases and th...
Yiping Ke, James Cheng, Wilfred Ng
CVPR
2008
IEEE
16 years 8 months ago
A discriminatively trained, multiscale, deformable part model
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the b...
Pedro F. Felzenszwalb, David A. McAllester, Deva R...
IEEEARES
2007
IEEE
16 years 12 days ago
Near Optimal Protection Strategies Against Targeted Attacks on the Core Node of a Network
The issue of information security has attracted increasing attention in recent years. In network attack and defense scenarios, attackers and defenders constantly change their resp...
Frank Yeong-Sung Lin, Po-Hao Tsang, Yi-Luen Lin