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PR
2007
100views more  PR 2007»
13 years 9 months ago
Linear manifold clustering in high dimensional spaces by stochastic search
Classical clustering algorithms are based on the concept that a cluster center is a single point. Clusters which are not compact around a single point are not candidates for class...
Robert M. Haralick, Rave Harpaz
MMAS
2011
Springer
13 years 4 months ago
Scalable Bayesian Reduced-Order Models for Simulating High-Dimensional Multiscale Dynamical Systems
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
Phaedon-Stelios Koutsourelakis, Elias Bilionis
NIPS
2001
13 years 11 months ago
Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines
A mixed-signal paradigm is presented for high-resolution parallel innerproduct computation in very high dimensions, suitable for efficient implementation of kernels in image proce...
Roman Genov, Gert Cauwenberghs
TIP
2008
177views more  TIP 2008»
13 years 9 months ago
Visual Tracking in High-Dimensional State Space by Appearance-Guided Particle Filtering
Abstract--In this paper, we propose a new approach, appearance-guided particle filtering (AGPF), for high degree-of-freedom visual tracking from an image sequence. This method adop...
Wen-Yan Chang, Chu-Song Chen, Yong-Dian Jian
EATCS
2000
67views more  EATCS 2000»
13 years 9 months ago
Low-Discrepancy Sets For High-Dimensional Rectangles: A Survey
A sub-area of discrepancy theory that has received much attention in computer science recently, is that of explicit constructions of low-discrepancy point sets for various types o...
A. Srinivasan