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TNN
2010
159views Management» more  TNN 2010»
14 years 9 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
103
Voted
ICCAD
2002
IEEE
143views Hardware» more  ICCAD 2002»
15 years 11 months ago
A Markov chain sequence generator for power macromodeling
In macromodeling-based power estimation, circuit macromodels are created from simulations of synthetic input vector sequences. Fast generation of these sequences with all possible...
Xun Liu, Marios C. Papaefthymiou
105
Voted
AINA
2009
IEEE
15 years 9 months ago
Improving Opportunistic Data Dissemination via Known Vector
An opportunistic network is a network where each node only has connectiviy with other nodes opportunistically. To disseminate data in this kind of network is a challenging task an...
Jyh-How Huang, Ying-Yu Chen, Yi-Chao Chen, Shivaka...
138
Voted
SIBGRAPI
2008
IEEE
15 years 9 months ago
Matching Photometric Observation Vectors with Shadows and Variable Albedo
We describe a procedure to solve the basic problem of Variable Lighting Photometric Stereo – namely, recovering the normal directions and intrinsic albedos at all visible points...
Helena Cristina da Gama Leitão, Rafael Feli...
CASC
2007
Springer
112views Mathematics» more  CASC 2007»
15 years 8 months ago
Polynomial Division Using Dynamic Arrays, Heaps, and Packed Exponent Vectors
A common way of implementing multivariate polynomial multiplication and division is to represent polynomials as linked lists of terms sorted in a term ordering and to use repeated ...
Michael B. Monagan, Roman Pearce