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PR
2007
100views more  PR 2007»
14 years 11 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
14 years 6 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
15 years 1 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»
14 years 11 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»
14 years 11 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