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» Evaluating algorithms that learn from data streams
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MLMI
2004
Springer
15 years 12 months ago
Multistream Dynamic Bayesian Network for Meeting Segmentation
This paper investigates the automatic analysis and segmentation of meetings. A meeting is analysed in terms of individual behaviours and group interactions, in order to decompose e...
Alfred Dielmann, Steve Renals
SSDBM
2008
IEEE
114views Database» more  SSDBM 2008»
16 years 28 days ago
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
Hans-Peter Kriegel, Peer Kröger, Erich Schube...
ICCV
2011
IEEE
14 years 6 months ago
Dynamic Manifold Warping for View Invariant Action Recognition
We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
Dian Gong, Gerard Medioni
JMLR
2006
97views more  JMLR 2006»
15 years 6 months ago
Learning Coordinate Covariances via Gradients
We introduce an algorithm that learns gradients from samples in the supervised learning framework. An error analysis is given for the convergence of the gradient estimated by the ...
Sayan Mukherjee, Ding-Xuan Zhou
ICML
2008
IEEE
16 years 7 months ago
Training restricted Boltzmann machines using approximations to the likelihood gradient
A new algorithm for training Restricted Boltzmann Machines is introduced. The algorithm, named Persistent Contrastive Divergence, is different from the standard Contrastive Diverg...
Tijmen Tieleman