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» Machine Learning of Temporal Relations
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145
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NIPS
2004
15 years 4 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
103
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MLG
2007
Springer
15 years 8 months ago
Weighted Substructure Mining for Image Analysis
1 In web-related applications of image categorization, it is desirable to derive an interpretable classification rule with high accuracy. Using the bag-of-words representation and...
Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku K...
125
Voted
GPEM
2008
128views more  GPEM 2008»
15 years 2 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood
123
Voted
CVPR
2009
IEEE
16 years 9 months ago
Co-training with Noisy Perceptual Observations
Many perception and multimedia indexing problems involve datasets that are naturally comprised of multiple streams or modalities for which supervised training data is only sparsely...
Ashish Kapoor, Chris Mario Christoudias, Raquel Ur...
121
Voted
KDD
2009
ACM
153views Data Mining» more  KDD 2009»
16 years 3 months ago
Predicting bounce rates in sponsored search advertisements
This paper explores an important and relatively unstudied quality measure of a sponsored search advertisement: bounce rate. The bounce rate of an ad can be informally defined as t...
D. Sculley, Robert G. Malkin, Sugato Basu, Roberto...