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KDD
2006
ACM
163views Data Mining» more  KDD 2006»
16 years 8 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper
ICIAP
2007
ACM
16 years 7 months ago
Adaptive uncertainty estimation for particle filter-based trackers
In particle filter?based visual trackers, dynamic velocity components are typically incorporated into the state update equations. In these cases, there is a risk that the uncertai...
Andrew D. Bagdanov, Alberto Del Bimbo, Fabrizio Di...
ALT
2009
Springer
16 years 4 months ago
Complexity versus Agreement for Many Views
Abstract. The paper considers the problem of semi-supervised multiview classification, where each view corresponds to a Reproducing Kernel Hilbert Space. An algorithm based on co-...
Odalric-Ambrym Maillard, Nicolas Vayatis
ALT
2007
Springer
16 years 4 months ago
Learning Kernel Perceptrons on Noisy Data Using Random Projections
In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classific...
Guillaume Stempfel, Liva Ralaivola
ALT
2002
Springer
16 years 4 months ago
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Dmitry Gavinsky