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» The Complexity of Probabilistic EL
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ICPR
2010
IEEE
13 years 6 months ago
Adaptive Motion Model for Human Tracking Using Particle Filter
This paper presents a novel approach to model the complex motion of human using a probabilistic autoregressive moving average model. The parameters of the model are adaptively tun...
Mohammad Hossein Ghaeminia, Amir Hossein Shabani, ...
ICRA
2009
IEEE
175views Robotics» more  ICRA 2009»
13 years 5 months ago
A combination of particle filtering and deterministic approaches for multiple kernel tracking
Color-based tracking methods have proved to be efficient for their robustness qualities. The drawback of such global representation of an object is the lack of information on its s...
Céline Teuliere, Éric Marchand, Laur...
JMLR
2010
173views more  JMLR 2010»
13 years 2 months ago
Elliptical slice sampling
Many probabilistic models introduce strong dependencies between variables using a latent multivariate Gaussian distribution or a Gaussian process. We present a new Markov chain Mo...
Iain Murray, Ryan Prescott Adams, David J. C. MacK...
ICASSP
2011
IEEE
12 years 11 months ago
Full-covariance UBM and heavy-tailed PLDA in i-vector speaker verification
In this paper, we describe recent progress in i-vector based speaker verification. The use of universal background models (UBM) with full-covariance matrices is suggested and tho...
Pavel Matejka, Ondrej Glembek, Fabio Castaldo, M. ...
ICASSP
2011
IEEE
12 years 11 months ago
Outlier-aware robust clustering
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...