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    NIPS
    2003
    151views Information Technology» more  NIPS 2003»
    Kernel Dimensionality Reduction for Supervised Learning
    13 years 5 months ago
    Kernel Dimensionality Reduction for Supervised Learning
    Download  books.nips.cc
    We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
    Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
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    NIPS
    2001
    208views Information Technology» more  NIPS 2001»
    Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
    13 years 5 months ago
    Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
    Download  www.cs.utsa.edu
    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
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    NIPS
    2004
    103views Information Technology» more  NIPS 2004»
    Multiple Relational Embedding
    13 years 5 months ago
    Multiple Relational Embedding
    Download  www.cs.toronto.edu
    We describe a way of using multiple different types of similarity relationship to learn a low-dimensional embedding of a dataset. Our method chooses different, possibly overlappin...
    Roland Memisevic, Geoffrey E. Hinton
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    NIPS
    2004
    172views Information Technology» more  NIPS 2004»
    Proximity Graphs for Clustering and Manifold Learning
    13 years 5 months ago
    Proximity Graphs for Clustering and Manifold Learning
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    Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
    Miguel Á. Carreira-Perpiñán, ...
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    SDM
    2007
    SIAM
    108views Data Mining» more  SDM 2007»
    Semi-Supervised Dimensionality Reduction
    13 years 5 months ago
    Semi-Supervised Dimensionality Reduction
    Download  cs.nju.edu.cn
    Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
    Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
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    SDM
    2007
    SIAM
    133views Data Mining» more  SDM 2007»
    On Point Sampling Versus Space Sampling for Dimensionality Reduction
    13 years 5 months ago
    On Point Sampling Versus Space Sampling for Dimensionality Reduction
    Download  www.charuaggarwal.net
    In recent years, random projection has been used as a valuable tool for performing dimensionality reduction of high dimensional data. Starting with the seminal work of Johnson and...
    Charu C. Aggarwal
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    RSS
    2007
    152views Robotics» more  RSS 2007»
    Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
    13 years 5 months ago
    Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
    Download  www.vision.caltech.edu
    Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
    Anelia Angelova, Larry Matthies, Daniel M. Helmick...
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    NIPS
    2007
    171views Information Technology» more  NIPS 2007»
    Locality and low-dimensions in the prediction of natural experience from fMRI
    13 years 5 months ago
    Locality and low-dimensions in the prediction of natural experience from fMRI
    Download  books.nips.cc
    Functional Magnetic Resonance Imaging (fMRI) provides dynamical access into the complex functioning of the human brain, detailing the hemodynamic activity of thousands of voxels d...
    Francois Meyer, Greg Stephens
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    NIPS
    2008
    207views Information Technology» more  NIPS 2008»
    DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
    13 years 5 months ago
    DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
    Download  www.cs.berkeley.edu
    Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
    Simon Lacoste-Julien, Fei Sha, Michael I. Jordan
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    NIPS
    2008
    205views Information Technology» more  NIPS 2008»
    Dimensionality Reduction for Data in Multiple Feature Representations
    13 years 5 months ago
    Dimensionality Reduction for Data in Multiple Feature Representations
    Download  www.csie.ntu.edu.tw
    In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
    Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
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