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» The Generalized Dimensionality Reduction Problem
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BMCBI
2006
202views more  BMCBI 2006»
14 years 10 months ago
Spectral embedding finds meaningful (relevant) structure in image and microarray data
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
CVPR
2003
IEEE
15 years 12 months ago
Nearest Neighbor Search for Relevance Feedback
We introduce the problem of repetitive nearest neighbor search in relevance feedback and propose an efficient search scheme for high dimensional feature spaces. Relevance feedback...
Jelena Tesic, B. S. Manjunath
ACL
2012
13 years 10 days ago
Fast Online Training with Frequency-Adaptive Learning Rates for Chinese Word Segmentation and New Word Detection
We present a joint model for Chinese word segmentation and new word detection. We present high dimensional new features, including word-based features and enriched edge (label-tra...
Xu Sun, Houfeng Wang, Wenjie Li
JSAC
2000
134views more  JSAC 2000»
14 years 9 months ago
Adaptive multidimensional coded modulation over flat fading channels
We introduce a general adaptive coding scheme for Nakagami multipath fading channels. An instance of the coding scheme utilizes a set of 2 -dimensional (2 -D) trellis codes origina...
Kjell Jørgen Hole, Henrik Holm, Geir E. &Os...
FOCS
2003
IEEE
15 years 3 months ago
Bounded Geometries, Fractals, and Low-Distortion Embeddings
The doubling constant of a metric space (X, d) is the smallest value λ such that every ball in X can be covered by λ balls of half the radius. The doubling dimension of X is the...
Anupam Gupta, Robert Krauthgamer, James R. Lee