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CGF
2011
14 years 5 months ago
Visualizing High-Dimensional Structures by Dimension Ordering and Filtering using Subspace Analysis
High-dimensional data visualization is receiving increasing interest because of the growing abundance of highdimensional datasets. To understand such datasets, visualization of th...
Bilkis J. Ferdosi, Jos B. T. M. Roerdink
SDM
2009
SIAM
184views Data Mining» more  SDM 2009»
15 years 11 months ago
DensEst: Density Estimation for Data Mining in High Dimensional Spaces.
Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...
Emmanuel Müller, Ira Assent, Ralph Krieger, S...
ICASSP
2010
IEEE
15 years 2 months ago
An L1 criterion for dictionary learning by subspace identification
We propose an ℓ1 criterion for dictionary learning for sparse signal representation. Instead of directly searching for the dictionary vectors, our dictionary learning approach i...
Florent Jaillet, Rémi Gribonval, Mark D. Pl...
116
Voted
ICDM
2003
IEEE
184views Data Mining» more  ICDM 2003»
15 years 7 months ago
Analyzing High-Dimensional Data by Subspace Validity
We are proposing a novel method that makes it possible to analyze high dimensional data with arbitrary shaped projected clusters and high noise levels. At the core of our method l...
Amihood Amir, Reuven Kashi, Nathan S. Netanyahu, D...
134
Voted
ECCV
2010
Springer
15 years 4 months ago
Optimum Subspace Learning and Error Correction for Tensors
Confronted with the high-dimensional tensor-like visual data, we derive a method for the decomposition of an observed tensor into a low-dimensional structure plus unbounded but spa...