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NIPS
2001
15 years 5 months ago
Kernel Machines and Boolean Functions
We give results about the learnability and required complexity of logical formulae to solve classification problems. These results are obtained by linking propositional logic with...
Adam Kowalczyk, Alex J. Smola, Robert C. Williamso...
MVA
1996
167views Computer Vision» more  MVA 1996»
15 years 5 months ago
Applying a Dynamic Recognition Scheme for Vehicle Recognition in Many Object Traffic Scenes
An adaptive object recognition scheme for image sequences of many object scenes is described. The scheme is applied for t r d c object recognition under ego-motion. The recursive ...
Wlodzimierz Kasprzak, Heinrich Niemann
TKDE
2008
152views more  TKDE 2008»
15 years 4 months ago
SRDA: An Efficient Algorithm for Large-Scale Discriminant Analysis
Linear Discriminant Analysis (LDA) has been a popular method for extracting features that preserves class separability. The projection functions of LDA are commonly obtained by max...
Deng Cai, Xiaofei He, Jiawei Han
JMLR
2010
115views more  JMLR 2010»
14 years 11 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri
JMLR
2010
143views more  JMLR 2010»
14 years 11 months ago
Beware of the DAG!
Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a ...
A. Philip Dawid