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SDM
2010
SIAM
153views Data Mining» more  SDM 2010»
13 years 6 months ago
Reconstruction from Randomized Graph via Low Rank Approximation
The privacy concerns associated with data analysis over social networks have spurred recent research on privacypreserving social network analysis, particularly on privacypreservin...
Leting Wu, Xiaowei Ying, Xintao Wu
WWW
2004
ACM
14 years 5 months ago
Efficient pagerank approximation via graph aggregation
We present a framework for approximating random-walk based probability distributions over Web pages using graph aggregation. We (1) partition the Web's graph into classes of ...
Andrei Z. Broder, Ronny Lempel, Farzin Maghoul, Ja...
TSP
2008
103views more  TSP 2008»
13 years 4 months ago
Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches
Abstract--We present a versatile framework for tractable computation of approximate variances in large-scale Gaussian Markov random field estimation problems. In addition to its ef...
Dmitry M. Malioutov, Jason K. Johnson, Myung Jin C...
PAMI
2007
176views more  PAMI 2007»
13 years 4 months ago
Approximate Labeling via Graph Cuts Based on Linear Programming
A new framework is presented for both understanding and developing graph-cut based combinatorial algorithms suitable for the approximate optimization of a very wide class of MRFs ...
Nikos Komodakis, Georgios Tziritas
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 6 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...