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» Structured metric learning for high dimensional problems
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ICCV
2009
IEEE
16 years 4 months ago
Robust Fitting of Multiple Structures: The Statistical Learning Approach
We propose an unconventional but highly effective approach to robust fitting of multiple structures by using statistical learning concepts. We design a novel Mercer kernel for t...
Tat-Jun Chin, Hanzi Wang, David Suter
JMLR
2012
13 years 2 months ago
Metric and Kernel Learning Using a Linear Transformation
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
AAAI
2008
15 years 2 months ago
Interaction Structure and Dimensionality Reduction in Decentralized MDPs
Decentralized Markov Decision Processes are a powerful general model of decentralized, cooperative multi-agent problem solving. The high complexity of the general problem leads to...
Martin Allen, Marek Petrik, Shlomo Zilberstein
CORR
2007
Springer
116views Education» more  CORR 2007»
14 years 11 months ago
The Extended Edit Distance Metric
Similarity search is an important problem in information retrieval. This similarity is based on a distance. Symbolic representation of time series has attracted many researchers re...
Muhammad Marwan Muhammad Fuad, Pierre-Francois Mar...
ICASSP
2011
IEEE
14 years 3 months ago
Particle algorithms for filtering in high dimensional state spaces: A case study in group object tracking
We briefly present the current state-of-the-art approaches for group and extended object tracking with an emphasis on particle methods which have high potential to handle complex...
Lyudmila Mihaylova, Avishy Carmi