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» Graphs Without Large Complete Minors Are Quasi-Random
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KDD
2009
ACM
163views Data Mining» more  KDD 2009»
14 years 7 months ago
Large-scale graph mining using backbone refinement classes
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Andreas Maunz, Christoph Helma, Stefan Kramer
WEA
2005
Springer
91views Algorithms» more  WEA 2005»
14 years 24 days ago
The Necessity of Timekeeping in Adversarial Queueing
We study queueing strategies in the adversarial queueing model. Rather than discussing individual prominent queueing strategies we tackle the issue on a general level and analyze c...
Maik Weinard
TSP
2008
151views more  TSP 2008»
13 years 7 months ago
Convergence Analysis of Reweighted Sum-Product Algorithms
Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...
SIGMOD
2008
ACM
139views Database» more  SIGMOD 2008»
14 years 7 months ago
Paths to stardom: calibrating the potential of a peer-based data management system
As peer-to-peer (P2P) networks become more familiar to the database community, intense interest has built up in using their scalability and resilience properties to scale database...
Mihai Lupu, Beng Chin Ooi, Y. C. Tay
SIGIR
2008
ACM
13 years 7 months ago
Learning query intent from regularized click graphs
This work presents the use of click graphs in improving query intent classifiers, which are critical if vertical search and general-purpose search services are to be offered in a ...
Xiao Li, Ye-Yi Wang, Alex Acero