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» Hierarchical Gaussian process latent variable models
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NIPS
2008
15 years 1 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
SADM
2008
106views more  SADM 2008»
14 years 11 months ago
Harmonium Models for Video Classification
: Accurate and efficient video classification demands the fusion of multimodal information and the use of intermediate representations. Combining the two ideas into one framework, ...
Jun Yang 0003, Rong Yan, Yan Liu, Eric P. Xing
MLMI
2007
Springer
15 years 5 months ago
Using Prosodic Features in Language Models for Meetings
Abstract. Prosody has been actively studied as an important knowledge source for speech recognition and understanding. In this paper, we are concerned with the question of exploiti...
Songfang Huang, Steve Renals
DAGM
2009
Springer
15 years 6 months ago
Deformation-Aware Log-Linear Models
Abstract. In this paper, we present a novel deformation-aware discriminative model for handwritten digit recognition. Unlike previous approaches our model directly considers image ...
Tobias Gass, Thomas Deselaers, Hermann Ney
NECO
2002
104views more  NECO 2002»
14 years 11 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen