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ICIP
2010
IEEE
8 years 11 months ago
Texture classification via patch-based sparse texton learning
Texture classification is a classical yet still active topic in computer vision and pattern recognition. Recently, several new texture classification approaches by modeling textur...
Jin Xie, Lei Zhang, Jane You, David Zhang
NIPS
2001
9 years 2 months ago
Global Coordination of Local Linear Models
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinto...
NIPS
2001
9 years 2 months ago
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
Mikhail Belkin, Partha Niyogi
AAAI
2007
9 years 3 months ago
Isometric Projection
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
Deng Cai, Xiaofei He, Jiawei Han
ICML
2004
IEEE
9 years 7 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
ISBI
2006
IEEE
10 years 2 months ago
Nonlinear classification of EEG data for seizure detection
We address the problem of classification of EEG recordings for the detection of epileptic seizures. We assume that the EEG measurements can be described by a low dimensional manif...
Mabel Ramírez-Vélez, Richard Staba, ...
ICML
2009
IEEE
10 years 2 months ago
Geometry-aware metric learning
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon
IPMI
2005
Springer
10 years 2 months ago
Analysis of Event-Related fMRI Data Using Diffusion Maps
The blood oxygen level-dependent (BOLD) signal in response to brief periods of stimulus can be detected using event-related functional magnetic resonance imaging (ER-fMRI). In this...
François G. Meyer, Xilin Shen
CVPR
2006
IEEE
10 years 3 months ago
Dimensionality Reduction by Learning an Invariant Mapping
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
Raia Hadsell, Sumit Chopra, Yann LeCun
CVPR
2005
IEEE
10 years 3 months ago
Tangent-Corrected Embedding
Images and other high-dimensional data can frequently be characterized by a low dimensional manifold (e.g. one that corresponds to the degrees of freedom of the camera). Recently,...
Ali Ghodsi, Jiayuan Huang, Finnegan Southey, Dale ...
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