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» Learning Classifiers from Semantically Heterogeneous Data
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TKDE
2008
195views more  TKDE 2008»
13 years 10 months ago
Learning a Maximum Margin Subspace for Image Retrieval
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
Xiaofei He, Deng Cai, Jiawei Han
DATAMINE
2002
169views more  DATAMINE 2002»
13 years 10 months ago
Advances in Instance Selection for Instance-Based Learning Algorithms
The basic nearest neighbour classifier suffers from the indiscriminate storage of all presented training instances. With a large database of instances classification response time ...
Henry Brighton, Chris Mellish
ICDM
2010
IEEE
160views Data Mining» more  ICDM 2010»
13 years 8 months ago
A Privacy Preserving Framework for Gaussian Mixture Models
Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
Madhusudana Shashanka
KDD
2010
ACM
222views Data Mining» more  KDD 2010»
14 years 6 days ago
Large linear classification when data cannot fit in memory
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...
Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-J...
ICPR
2010
IEEE
13 years 8 months ago
Data Classification on Multiple Manifolds
Unlike most previous manifold-based data classification algorithms assume that all the data points are on a single manifold, we expect that data from different classes may reside ...
Rui Xiao, Qijun Zhao, David Zhang, Pengfei Shi