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138
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ICML
2007
IEEE
16 years 4 months ago
Hierarchical Gaussian process latent variable models
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
Neil D. Lawrence, Andrew J. Moore
127
Voted
HICSS
2006
IEEE
123views Biometrics» more  HICSS 2006»
15 years 9 months ago
SeamCAD: Object-Oriented Modeling Tool for Hierarchical Systems in Enterprise Architecture
Enterprise Architecture (EA) requires modeling enterprises across multiple levels (from markets down to IT systems). Providing tool support for such models is a challenge (e.g. mo...
Lam-Son Lê, Alain Wegmann
163
Voted
ICIP
2007
IEEE
16 years 5 months ago
Hierarchical Feature Fusion for Visual Tracking
A new method for object tracking in video sequences is presented. This method exploits the benefits of particle filters to tackle the multimodal distributions emerging from clutte...
Alexandros Makris, Dimitrios I. Kosmopoulos, Stavr...
105
Voted
ICCAD
2006
IEEE
95views Hardware» more  ICCAD 2006»
16 years 20 days ago
Timing model reduction for hierarchical timing analysis
— In this paper, we propose a timing model reduction algorithm for hierarchical timing analysis based on a bicliquestar replacement technique. In hierarchical timing analysis, ea...
Shuo Zhou, Yi Zhu, Yuanfang Hu, Ronald L. Graham, ...
TASLP
2010
97views more  TASLP 2010»
14 years 10 months ago
Hierarchical Bayesian Language Models for Conversational Speech Recognition
Traditional n-gram language models are widely used in state-of-the-art large vocabulary speech recognition systems. This simple model suffers from some limitations, such as overfi...
Songfang Huang, Steve Renals