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» Learning Mixtures of Gaussians
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PCI
2005
Springer
14 years 1 months ago
Unsupervised Learning of Multiple Aspects of Moving Objects from Video
A popular framework for the interpretation of image sequences is based on the layered model; see e.g. Wang and Adelson [8], Irani et al. [2]. Jojic and Frey [3] provide a generativ...
Michalis K. Titsias, Christopher K. I. Williams
NIPS
2004
13 years 9 months ago
Sampling Methods for Unsupervised Learning
We present an algorithm to overcome the local maxima problem in estimating the parameters of mixture models. It combines existing approaches from both EM and a robust fitting algo...
Robert Fergus, Andrew Zisserman, Pietro Perona
CORR
2010
Springer
124views Education» more  CORR 2010»
13 years 8 months ago
Online Learning of Noisy Data with Kernels
We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
RAS
2010
216views more  RAS 2010»
13 years 6 months ago
A nonparametric learning approach to range sensing from omnidirectional vision
We present a novel approach to estimating depth from single omnidirectional camera images by learning the relationship between visual features and range measurements available dur...
Christian Plagemann, Cyrill Stachniss, Jürgen...
ICCV
2001
IEEE
14 years 10 months ago
Learning Inhomogeneous Gibbs Model of Faces by Minimax Entropy
In this paper we propose a novel inhomogeneous Gibbs model by the minimax entropy principle, and apply it to face modeling. The maximum entropy principle generalizes the statistic...
Ce Liu, Song Chun Zhu, Heung-Yeung Shum