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93
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SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
15 years 10 months ago
Top-k Correlative Graph Mining.
Correlation mining has been widely studied due to its ability for discovering the underlying occurrence dependency between objects. However, correlation mining in graph databases ...
Yiping Ke, James Cheng, Jeffrey Xu Yu
115
Voted
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
15 years 2 months ago
Maximal Quasi-Bicliques with Balanced Noise Tolerance: Concepts and Co-clustering Applications
The rigid all-versus-all adjacency required by a maximal biclique for its two vertex sets is extremely vulnerable to missing data. In the past, several types of quasi-bicliques ha...
Jinyan Li, Kelvin Sim, Guimei Liu, Limsoon Wong
SIAMSC
2008
182views more  SIAMSC 2008»
15 years 22 days ago
A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation
We propose a distributed algorithm for solving Euclidean metric realization problems arising from large 3D graphs, using only noisy distance information, and without any prior kno...
Pratik Biswas, Kim-Chuan Toh, Yinyu Ye
132
Voted
PAMI
2010
260views more  PAMI 2010»
14 years 11 months ago
Unsupervised Object Segmentation with a Hybrid Graph Model (HGM)
—In this work, we address the problem of performing class-specific unsupervised object segmentation, i.e., automatic segmentation without annotated training images. Object segmen...
Guangcan Liu, Zhouchen Lin, Yong Yu, Xiaoou Tang
CVPR
2010
IEEE
15 years 9 months ago
Beyond Trees: MRF Inference via Outer-Planar Decomposition
Maximum a posteriori (MAP) inference in Markov Random Fields (MRFs) is an NP-hard problem, and thus research has focussed on either finding efficiently solvable subclasses (e.g. t...
Dhruv Batra, Andrew Gallagher, Devi Parikh, Tsuhan...