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» Learning a Distance Metric from Relative Comparisons
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STOC
2005
ACM
130views Algorithms» more  STOC 2005»
16 years 3 months ago
Low-distortion embeddings of general metrics into the line
A low-distortion embedding between two metric spaces is a mapping which preserves the distances between each pair of points, up to a small factor called distortion. Low-distortion...
Mihai Badoiu, Julia Chuzhoy, Piotr Indyk, Anastasi...
ICPR
2010
IEEE
15 years 1 months ago
Unsupervised Learning from Linked Documents
Documents in many corpora, such as digital libraries and webpages, contain both content and link information. In a traditional topic model which plays an important role in the uns...
Zhen Guo, Shenghuo Zhu, Yun Chi, Zhongfei Zhang, Y...
SSPR
2010
Springer
15 years 1 months ago
An Empirical Comparison of Kernel-Based and Dissimilarity-Based Feature Spaces
The aim of this paper is to find an answer to the question: What is the difference between dissimilarity-based classifications(DBCs) and other kernelbased classifications(KBCs)?...
Sang-Woon Kim, Robert P. W. Duin
AI
1998
Springer
15 years 7 months ago
Sequential Instance-Based Learning
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
Susan L. Epstein, Jenngang Shih
ICCV
2007
IEEE
16 years 5 months ago
An Invariant Large Margin Nearest Neighbour Classifier
The k-nearest neighbour (kNN) rule is a simple and effective method for multi-way classification that is much used in Computer Vision. However, its performance depends heavily on ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...