Sciweavers

ICASSP
2011
IEEE
12 years 8 months ago
Mixture Kalman filtering for joint carrier recovery and channel estimation in time-selective Rayleigh fading channels
This paper proposes a new blind algorithm, based on Mixture Kalman Filtering (MKF), for joint carrier recovery and channel estimation in time-selective Rayleigh fading channels. M...
Ali A. Nasir, Salman Durrani, Rodney A. Kennedy
JMLR
2010
184views more  JMLR 2010»
12 years 11 months ago
Sequential Monte Carlo Samplers for Dirichlet Process Mixtures
In this paper, we develop a novel online algorithm based on the Sequential Monte Carlo (SMC) samplers framework for posterior inference in Dirichlet Process Mixtures (DPM) (DelMor...
Yener Ülker, Bilge Günsel, Ali Taylan Ce...
SAC
2008
ACM
13 years 4 months ago
Adaptive methods for sequential importance sampling with application to state space models
Abstract. In this paper we discuss new adaptive proposal strategies for sequential Monte Carlo algorithms--also known as particle filters--relying on new criteria evaluating the qu...
Julien Cornebise, Eric Moulines, Jimmy Olsson
SAC
2008
ACM
13 years 4 months ago
Particle methods for maximum likelihood estimation in latent variable models
Standard methods for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo variants. Our approach is ...
Adam M. Johansen, Arnaud Doucet, Manuel Davy
CGF
2008
129views more  CGF 2008»
13 years 4 months ago
Sequential Monte Carlo Adaptation in Low-Anisotropy Participating Media
This paper presents a novel method that effectively combines both control variates and importance sampling in a sequential Monte Carlo context. The radiance estimates computed dur...
Vincent Pegoraro, Ingo Wald, Steven G. Parker
NIPS
1998
13 years 5 months ago
Global Optimisation of Neural Network Models via Sequential Sampling
We propose a novel strategy for training neural networks using sequential Monte Carlo algorithms. This global optimisation strategy allows us to learn the probability distribution...
João F. G. de Freitas, Mahesan Niranjan, Ar...
NIPS
2008
13 years 6 months ago
An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering
We propose an efficient sequential Monte Carlo inference scheme for the recently proposed coalescent clustering model [1]. Our algorithm has a quadratic runtime while those in [1]...
Dilan Görür, Yee Whye Teh
AUSDM
2008
Springer
224views Data Mining» more  AUSDM 2008»
13 years 6 months ago
Customer Event Rate Estimation Using Particle Filters
Estimating the rate at which events happen has been studied under various guises and in different settings. We are interested in the specific case of consumerinitiated events or t...
Harsha Honnappa
ICPR
2002
IEEE
13 years 9 months ago
A Robust Algorithm for Probabilistic Human Recognition From
Human recognition from video requires solving the two tasks, recognition and tracking, simultaneously. This leads to a parameterized time series state space model, representing bo...
Shaohua Kevin Zhou, Rama Chellappa
AMFG
2003
IEEE
113views Biometrics» more  AMFG 2003»
13 years 9 months ago
Sequential Monte Carlo Tracking of Body Parameters in a Sub-Space
In recent years Sequential Monte Carlo (SMC) methods have been applied to handle some of the problems inherent to model-based tracking. In this paper two issues regarding SMC are ...
Thomas B. Moeslund, Erik Granum