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ICASSP
2011
IEEE
12 years 11 months ago
Stochastic behavior analysis of the Gaussian Kernel Least Mean Square algorithm
Like its linear counterpart, the Kernel Least Mean Square (KLMS) algorithm is also becoming popular in nonlinear adaptive filtering due to its simplicity and robustness. The “k...
Wemerson D. Parreira, José Carlos M. Bermud...
JMLR
2010
112views more  JMLR 2010»
13 years 2 months ago
Sparse Spectrum Gaussian Process Regression
We present a new sparse Gaussian Process (GP) model for regression. The key novel idea is to sparsify the spectral representation of the GP. This leads to a simple, practical algo...
Miguel Lázaro-Gredilla, Joaquin Quiñ...
ICASSP
2011
IEEE
12 years 11 months ago
Motion vector recovery with Gaussian Process Regression
In this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem...
Hadi Asheri, Abdolkhalegh Bayati, Hamid R. Rabiee,...
JMLR
2010
150views more  JMLR 2010»
13 years 2 months ago
Approximate parameter inference in a stochastic reaction-diffusion model
We present an approximate inference approach to parameter estimation in a spatio-temporal stochastic process of the reaction-diffusion type. The continuous space limit of an infer...
Andreas Ruttor, Manfred Opper
ICML
2010
IEEE
13 years 8 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre