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» Hierarchical Gaussian process latent variable models
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ICASSP
2008
IEEE
15 years 6 months ago
Sparse and shift-invariant feature extraction from non-negative data
In this paper we describe a technique that allows the extraction of multiple local shift-invariant features from analysis of non-negative data of arbitrary dimensionality. Our app...
Paris Smaragdis, Bhiksha Raj, Madhusudana V. S. Sh...
KDD
2012
ACM
244views Data Mining» more  KDD 2012»
13 years 2 months ago
Open domain event extraction from twitter
Tweets are the most up-to-date and inclusive stream of information and commentary on current events, but they are also fragmented and noisy, motivating the need for systems that c...
Alan Ritter, Mausam, Oren Etzioni, Sam Clark
ICASSP
2011
IEEE
14 years 3 months ago
Enhanced Poisson sum representation for alpha-stable processes
In this paper we present Poisson sum series representations for α-stable (αS) random variables and α-stable processes, in particular concentrating on continuous-time autoregres...
Tatjana Lemke, Simon J. Godsill
ICMI
2010
Springer
220views Biometrics» more  ICMI 2010»
14 years 9 months ago
Visual speech synthesis by modelling coarticulation dynamics using a non-parametric switching state-space model
We present a novel approach to speech-driven facial animation using a non-parametric switching state space model based on Gaussian processes. The model is an extension of the shar...
Salil Deena, Shaobo Hou, Aphrodite Galata
ICASSP
2011
IEEE
14 years 3 months ago
Multivariate texture retrieval using the SIRV representation and the geodesic distance
This paper presents a new wavelet based retrieval approach based on Spherically Invariant Random Vector (SIRV) modeling of wavelet subbands. Under this multivariate model, wavelet...
Lionel Bombrun, Noureddine Lasmar, Yannick Berthou...