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» The intrinsic dimensionality of graphs
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TNN
2008
105views more  TNN 2008»
14 years 9 months ago
Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
Shuiwang Ji, Jieping Ye
72
Voted
ICPR
2006
IEEE
15 years 10 months ago
A Semi-supervised SVM for Manifold Learning
Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
Zhili Wu, Chun-hung Li, Ji Zhu, Jian Huang
GLVLSI
2009
IEEE
159views VLSI» more  GLVLSI 2009»
15 years 4 months ago
On the complexity of graph cuboidal dual problems for 3-D floorplanning of integrated circuit design
This paper discusses the impact of migrating from 2-D to 3-D on floorplanning and placement. By looking at a basic formulation of graph cuboidal dual problem, we show that the 3-...
Renshen Wang, Chung-Kuan Cheng
56
Voted
ICTAI
2008
IEEE
15 years 4 months ago
FIP: A Fast Planning-Graph-Based Iterative Planner
We present a fast iterative planner (FIP) that aims to handle planning problems involving nondeterministic actions. In contrast to existing iterative planners, FIP is built upon G...
Jicheng Fu, Farokh B. Bastani, Vincent Ng, I-Ling ...
72
Voted
AIRS
2006
Springer
15 years 1 months ago
Natural Document Clustering by Clique Percolation in Random Graphs
Document clustering techniques mostly depend on models that impose explicit and/or implicit priori assumptions as to the number, size, disjunction characteristics of clusters, and/...
Wei Gao, Kam-Fai Wong