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KDD
2010
ACM
197views Data Mining» more  KDD 2010»
15 years 4 months ago
Semi-supervised feature selection for graph classification
The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Xiangnan Kong, Philip S. Yu
SDM
2007
SIAM
126views Data Mining» more  SDM 2007»
15 years 8 months ago
Nonlinear Dimensionality Reduction using Approximate Nearest Neighbors
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
Erion Plaku, Lydia E. Kavraki
FCCM
2006
IEEE
113views VLSI» more  FCCM 2006»
16 years 22 days ago
GraphStep: A System Architecture for Sparse-Graph Algorithms
— Many important applications are organized around long-lived, irregular sparse graphs (e.g., data and knowledge bases, CAD optimization, numerical problems, simulations). The gr...
Michael DeLorimier, Nachiket Kapre, Nikil Mehta, D...
ICML
2009
IEEE
16 years 7 months ago
Graph construction and b-matching for semi-supervised learning
Graph based semi-supervised learning (SSL) methods play an increasingly important role in practical machine learning systems. A crucial step in graph based SSL methods is the conv...
Tony Jebara, Jun Wang, Shih-Fu Chang
207
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DAGSTUHL
2001
15 years 8 months ago
An Overview of the GXL Graph Exchange Language
GXL (Graph eXchange Language) is designed to be a standard exchange format for graph-based tools. GXL is defined as an XML sublanguage, which offers support for exchanging instanc...
Andreas Winter, Bernt Kullbach, Volker Riediger