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IJCAI
2007
10 years 3 hour ago
Improving Embeddings by Flexible Exploitation of Side Information
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
Ali Ghodsi, Dana F. Wilkinson, Finnegan Southey
SDM
2010
SIAM
153views Data Mining» more  SDM 2010»
10 years 13 hour ago
The Generalized Dimensionality Reduction Problem
The dimensionality reduction problem has been widely studied in the database literature because of its application for concise data representation in a variety of database applica...
Charu C. Aggarwal
AAAI
2010
10 years 21 hour ago
Multi-Instance Dimensionality Reduction
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
Yu-Yin Sun, Michael K. Ng, Zhi-Hua Zhou
AAAI
2010
10 years 22 hour ago
Conformal Mapping by Computationally Efficient Methods
Dimensionality reduction is the process by which a set of data points in a higher dimensional space are mapped to a lower dimension while maintaining certain properties of these p...
Stefan Pintilie, Ali Ghodsi
CIVR
2008
Springer
271views Image Analysis» more  CIVR 2008»
10 years 11 days ago
Multiple feature fusion by subspace learning
Since the emergence of extensive multimedia data, feature fusion has been more and more important for image and video retrieval, indexing and annotation. Existing feature fusion t...
Yun Fu, Liangliang Cao, Guodong Guo, Thomas S. Hua...
CBMS
2005
IEEE
10 years 16 days ago
Local Dimensionality Reduction within Natural Clusters for Medical Data Analysis
Inductive learning systems have been successfully applied in a number of medical domains. Nevertheless, the effective use of these systems requires data preprocessing before apply...
Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen
KDD
2010
ACM
242views Data Mining» more  KDD 2010»
10 years 17 days ago
A scalable two-stage approach for a class of dimensionality reduction techniques
Dimensionality reduction plays an important role in many data mining applications involving high-dimensional data. Many existing dimensionality reduction techniques can be formula...
Liang Sun, Betul Ceran, Jieping Ye
ADMA
2008
Springer
124views Data Mining» more  ADMA 2008»
10 years 17 days ago
Dimensionality Reduction for Classification
We investigate the effects of dimensionality reduction using different techniques and different dimensions on six two-class data sets with numerical attributes as pre-processing fo...
Frank Plastria, Steven De Bruyne, Emilio Carrizosa
ACMACE
2008
ACM
10 years 17 days ago
Dimensionality reduced HRTFs: a comparative study
Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
Bill Kapralos, Nathan Mekuz, Agnieszka Kopinska, S...
AAAI
2007
10 years 27 days 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
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