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» Empirical comparison of graph classification algorithms
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PR
2008
131views more  PR 2008»
13 years 7 months ago
A memetic algorithm for evolutionary prototype selection: A scaling up approach
Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. ...
Salvador García, José Ramón C...
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 7 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
SIGMOD
2008
ACM
144views Database» more  SIGMOD 2008»
14 years 7 months ago
Mining significant graph patterns by leap search
With ever-increasing amounts of graph data from disparate sources, there has been a strong need for exploiting significant graph patterns with user-specified objective functions. ...
Xifeng Yan, Hong Cheng, Jiawei Han, Philip S. Yu
CVPR
2008
IEEE
14 years 9 months ago
Large-scale manifold learning
This paper examines the problem of extracting lowdimensional manifold structure given millions of highdimensional face images. Specifically, we address the computational challenge...
Ameet Talwalkar, Sanjiv Kumar, Henry A. Rowley
RECOMB
2007
Springer
14 years 7 months ago
An Efficient and Accurate Graph-Based Approach to Detect Population Substructure
Currently, large-scale projects are underway to perform whole genome disease association studies. Such studies involve the genotyping of hundreds of thousands of SNP markers. One o...
Srinath Sridhar, Satish Rao, Eran Halperin