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» Gaussian Processes in Reinforcement Learning
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ICASSP
2011
IEEE
14 years 1 months ago
Blind beamformer for constant modulus signals based on relevance vector machine
The blind beamforming method for constant modulus (CM) signals based on relevance vector machine (RVM) is proposed. The proposed beamforming method is obtained by incorporating th...
Kyuho Hwang, Sooyong Choi
EC
2006
121views ECommerce» more  EC 2006»
14 years 9 months ago
A Study of Structural and Parametric Learning in XCS
The performance of a learning classifier system is due to its two main components. First, it evolves new structures by generating new rules in a genetic process; second, it adjust...
Tim Kovacs, Manfred Kerber
JMLR
2010
202views more  JMLR 2010»
14 years 4 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
ICIP
2007
IEEE
15 years 11 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian
AVSS
2009
IEEE
15 years 1 months ago
Bayesian Bio-inspired Model for Learning Interactive Trajectories
—Automatic understanding of human behavior is an important and challenging objective in several surveillance applications. One of the main problems of this task consists in accur...
Alessio Dore, Carlo S. Regazzoni