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ECCV
2010
Springer
13 years 10 months ago
Weakly-Paired Maximum Covariance Analysis for Multimodal Dimensionality Reduction and Transfer
Abstract. We study the problem of multimodal dimensionality reduction assuming that data samples can be missing at training time, and not all data modalities may be present at appl...
ICML
2006
IEEE
14 years 6 months ago
Local distance preservation in the GP-LVM through back constraints
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
Joaquin Quiñonero Candela, Neil D. Lawrence
PAMI
2008
182views more  PAMI 2008»
13 years 5 months ago
Gaussian Process Dynamical Models for Human Motion
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
IFIP12
2009
13 years 3 months ago
User Recommendations based on Tensor Dimensionality Reduction
Social Tagging is the process by which many users add metadata in the form of keywords, to annotate and categorize items (songs, pictures, web links, products etc.). Social tagging...
Panagiotis Symeonidis
BMCBI
2010
122views more  BMCBI 2010»
13 years 5 months ago
Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data
Background: Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduc...
Kai-Lin Tang, Tong-Hua Li, Wen-Wei Xiong, Kai Chen