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» Extractive summarization using a latent variable model
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ICMCS
2005
IEEE
88views Multimedia» more  ICMCS 2005»
15 years 3 months ago
Spoken document summarization using acoustic, prosodic and semantic information
This paper presents a spoken document summarization scheme using acoustic, prosodic and semantic information. First, speech recognition confidence is estimated to choose reliable ...
Chien-Lin Huang, Chia-Hsin Hsieh, Chung-Hsien Wu
NIPS
2007
14 years 11 months ago
Convex Relaxations of Latent Variable Training
We investigate a new, convex relaxation of an expectation-maximization (EM) variant that approximates a standard objective while eliminating local minima. First, a cautionary resu...
Yuhong Guo, Dale Schuurmans
ICIP
2006
IEEE
15 years 11 months ago
Unsupervised Image Layout Extraction
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...
David Liu, Datong Chen, Tsuhan Chen
ICPR
2008
IEEE
15 years 4 months ago
Tracking human body by using particle filter Gaussian process Markov-switching model
The goal of this article is to present an effective and robust tracking algorithm for nonlinear feet motion by deploying particle filter integrated with Gaussian process latent v...
Jing Wang, Hong Man, Yafeng Yin
PAMI
2011
14 years 4 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams