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» Hierarchical Gaussian process latent variable models
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WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
15 years 9 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
ICASSP
2010
IEEE
14 years 12 months ago
An adaptive initialization method for speaker Diarization based on prosodic features
The following article presents a novel, adaptive initialization scheme that can be applied to most state-of-the-art Speaker Diarization algorithms, i.e. algorithms that use agglom...
David Imseng, Gerald Friedland
108
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BMVC
2010
14 years 9 months ago
Background Modelling on Tensor Field for Foreground Segmentation
The paper proposes a new method to perform foreground detection by means of background modeling using the tensor concept. Sometimes, statistical modelling directly on image values...
Rui Caseiro, Jorge Batista, Pedro Martins
ICCD
2006
IEEE
157views Hardware» more  ICCD 2006»
15 years 8 months ago
Statistical Analysis of Power Grid Networks Considering Lognormal Leakage Current Variations with Spatial Correlation
— As the technology scales into 90nm and below, process-induced variations become more pronounced. In this paper, we propose an efficient stochastic method for analyzing the vol...
Ning Mi, Jeffrey Fan, Sheldon X.-D. Tan
99
Voted
NECO
2002
145views more  NECO 2002»
14 years 11 months ago
Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
Aki Vehtari, Jouko Lampinen