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KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 8 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
DMIN
2008
158views Data Mining» more  DMIN 2008»
13 years 9 months ago
Mining User Movement Behavior Patterns in a Mobile Service Environment
Abstract - The rapid advances of wireless and web technologies enable the mobile users to request various kinds of services via mobile devices at anytime and anywhere. To provide t...
Yen-Ssu Chou, Tzung-Shi Chen
SISAP
2008
IEEE
188views Data Mining» more  SISAP 2008»
14 years 2 months ago
High-Dimensional Similarity Retrieval Using Dimensional Choice
There are several pieces of information that can be utilized in order to improve the efficiency of similarity searches on high-dimensional data. The most commonly used information...
Dave Tahmoush, Hanan Samet
NIPS
2004
13 years 9 months ago
Hierarchical Eigensolver for Transition Matrices in Spectral Methods
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
Chakra Chennubhotla, Allan D. Jepson
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 8 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley