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» Adaptive Distance Metric Learning for Clustering
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KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 7 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
NPL
2006
172views more  NPL 2006»
13 years 7 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
ICAC
2007
IEEE
14 years 1 months ago
Adaptive Learning of Metric Correlations for Temperature-Aware Database Provisioning
This paper introduces a transparent self-configuring architecture for automatic scaling with temperature awareness in the database tier of a dynamic content web server. We use a ...
Saeed Ghanbari, Gokul Soundararajan, Jin Chen, Cri...
ICML
2003
IEEE
14 years 8 months ago
Learning Distance Functions using Equivalence Relations
We address the problem of learning distance metrics using side-information in the form of groups of "similar" points. We propose to use the RCA algorithm, which is a sim...
Aharon Bar-Hillel, Tomer Hertz, Noam Shental, Daph...
ECML
2007
Springer
14 years 1 months ago
Learning Metrics Between Tree Structured Data: Application to Image Recognition
The problem of learning metrics between structured data (strings, trees or graphs) has been the subject of various recent papers. With regard to the specific case of trees, some a...
Laurent Boyer 0002, Amaury Habrard, Marc Sebban