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» Semi-Supervised Learning of Mixture Models
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ICCS
2007
Springer
15 years 6 months ago
Towards Real-Time Distributed Signal Modeling for Brain-Machine Interfaces
New architectures for Brain-Machine Interface communication and control use mixture models for expanding rehabilitation capabilities of disabled patients. Here we present and test ...
Jack DiGiovanna, Loris Marchal, Prapaporn Rattanat...
ECML
2007
Springer
15 years 6 months ago
Spectral Clustering and Embedding with Hidden Markov Models
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
Tony Jebara, Yingbo Song, Kapil Thadani
COGSR
2011
109views more  COGSR 2011»
14 years 6 months ago
How groups develop a specialized domain vocabulary: A cognitive multi-agent model
We simulate the evolution of a domain vocabulary in small communities. Empirical data show that human communicators can evolve graphical languages quickly in a constrained task (P...
David Reitter, Christian Lebiere
ICML
2010
IEEE
15 years 25 days ago
Variable Selection in Model-Based Clustering: To Do or To Facilitate
Variable selection for cluster analysis is a difficult problem. The difficulty originates not only from the lack of class information but also the fact that high-dimensional data ...
Leonard K. M. Poon, Nevin Lianwen Zhang, Tao Chen,...
CVPR
2000
IEEE
16 years 1 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona