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NIPS
2003
9 years 6 months ago
Hierarchical Topic Models and the Nested Chinese Restaurant Process
We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
ESANN
2006
9 years 6 months ago
Degeneracy in model selection for SVMs with radial Gaussian kernel
We consider the model selection problem for support vector machines applied to binary classification. As the data generating process is unknown, we have to rely on heuristics as mo...
Tobias Glasmachers
HYBRID
2000
Springer
9 years 9 months ago
Hybrid Systems Diagnosis
This paper reports on an on-going project to investigate techniques to diagnose complex dynamical systems that are modeled as hybrid systems. In particular, we examine continuous s...
Sheila A. McIlraith, Gautam Biswas, Dan Clancy, Vi...
DAGM
2006
Springer
9 years 9 months ago
Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Mikio L. Braun, Tilman Lange, Joachim M. Buhmann
ICRA
2009
IEEE
123views Robotics» more  ICRA 2009»
10 years 4 days ago
Tracking groups of people with a multi-model hypothesis tracker
Abstract— People in densely populated environments typically form groups that split and merge. In this paper we track groups of people so as to reflect this formation process an...
Boris Lau, Kai Oliver Arras, Wolfram Burgard
ICML
2009
IEEE
10 years 6 months ago
Optimized expected information gain for nonlinear dynamical systems
This paper addresses the problem of active model selection for nonlinear dynamical systems. We propose a novel learning approach that selects the most informative subset of time-d...
Alberto Giovanni Busetto, Cheng Soon Ong, Joachim ...
ICCV
2001
IEEE
10 years 7 months ago
Topology Free Hidden Markov Models: Application to Background Modeling
Hidden Markov Models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Th...
Bjoern Stenger, Visvanathan Ramesh, Nikos Paragios...
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