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» The Feature Selection Path in Kernel Methods
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ICANN
2007
Springer
14 years 1 months ago
Incremental and Decremental Learning for Linear Support Vector Machines
Abstract. We present a method to find the exact maximal margin hyperplane for linear Support Vector Machines when a new (existing) component is added (removed) to (from) the inner...
Enrique Romero, Ignacio Barrio, Lluís Belan...
DAC
1998
ACM
14 years 8 months ago
Functional Vector Generation for HDL Models Using Linear Programming and 3-Satisfiability
Abstract-Our strategy for automatic generation of functional vectors is based on exercising selected paths in the given hardware description language (HDL) model. The HDL model des...
Farzan Fallah, Srinivas Devadas, Kurt Keutzer
TVCG
2010
114views more  TVCG 2010»
13 years 5 months ago
Topology-Aware Evenly Spaced Streamline Placement
—This paper presents a new streamline placement algorithm that produces evenly spaced long streamlines while preserving topological features of a flow field. Singularities and se...
Keqin Wu, Zhanping Liu, Song Zhang, Robert J. Moor...
ICPR
2010
IEEE
13 years 5 months ago
Low-Level Image Segmentation Based Scene Classification
This paper is aimed at evaluating the semantic information content of multiscale, low-level image segmentation. As a method of doing this, we use selected features of segmentation...
Emre Akbas, Narendra Ahuja
KI
2007
Springer
13 years 7 months ago
Improving the Detection of Unknown Computer Worms Activity Using Active Learning
Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, after t...
Robert Moskovitch, Nir Nissim, Dima Stopel, Clint ...