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» A learning framework for nearest neighbor search
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MMM
2011
Springer
251views Multimedia» more  MMM 2011»
14 years 1 months ago
Randomly Projected KD-Trees with Distance Metric Learning for Image Retrieval
Abstract. Efficient nearest neighbor (NN) search techniques for highdimensional data are crucial to content-based image retrieval (CBIR). Traditional data structures (e.g., kd-tree...
Pengcheng Wu, Steven C. H. Hoi, Duc Dung Nguyen, Y...
PVLDB
2010
151views more  PVLDB 2010»
14 years 7 months ago
A Generic Framework for Handling Uncertain Data with Local Correlations
Data uncertainty is ubiquitous in many real-world applications such as sensor/RFID data analysis. In this paper, we investigate uncertain data that exhibit local correlations, tha...
Xiang Lian, Lei Chen 0002
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
15 years 9 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
TRECVID
2008
14 years 11 months ago
National Institute of Informatics, Japan at TRECVID 2008
This paper reports our experiments for TRECVID 2008 tasks: high level feature extraction, search and contentbased copy detection. For the high level feature extraction task, we use...
Duy-Dinh Le, Xiaomeng Wu, Shin'ichi Satoh, Sheetal...
ICML
1994
IEEE
15 years 29 days ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak