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ICDM
2002
IEEE
158views Data Mining» more  ICDM 2002»
15 years 7 months ago
Adaptive dimension reduction for clustering high dimensional data
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
ADC
2006
Springer
158views Database» more  ADC 2006»
15 years 8 months ago
Dimensionality reduction in patch-signature based protein structure matching
Searching bio-chemical structures is becoming an important application domain of information retrieval. This paper introduces a protein structure matching problem and formulates i...
Zi Huang, Xiaofang Zhou, Dawei Song, Peter Bruza
165
Voted
EDBT
2006
ACM
154views Database» more  EDBT 2006»
15 years 6 months ago
Approximation Techniques to Enable Dimensionality Reduction for Voronoi-Based Nearest Neighbor Search
Utilizing spatial index structures on secondary memory for nearest neighbor search in high-dimensional data spaces has been the subject of much research. With the potential to host...
Christoph Brochhaus, Marc Wichterich, Thomas Seidl
AAAI
2008
15 years 4 months ago
Transfer Learning via Dimensionality Reduction
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
Sinno Jialin Pan, James T. Kwok, Qiang Yang
115
Voted
ACAL
2007
Springer
15 years 4 months ago
Modelling Architectural Visual Experience Using Non-linear Dimensionality Reduction
This paper addresses the topic of how architectural visual experience can be represented and utilised by a software system. The long-term aim is to equip an artificial agent with ...
Stephan K. Chalup, Riley Clement, Chris Tucker, Mi...