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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 9 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
BMCBI
2010
229views more  BMCBI 2010»
13 years 9 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
MM
2010
ACM
137views Multimedia» more  MM 2010»
13 years 9 months ago
Self-diagnostic peer-assisted video streaming through a learning framework
Quality control and resource optimization are challenging problems in peer-assisted video streaming systems, due to their large scales and unreliable peer behavior. Such systems a...
Di Niu, Baochun Li, Shuqiao Zhao
BMCBI
2010
147views more  BMCBI 2010»
13 years 9 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
CIKM
2010
Springer
13 years 7 months ago
Selectively diversifying web search results
Search result diversification is a natural approach for tackling ambiguous queries. Nevertheless, not all queries are equally ambiguous, and hence different queries could bene...
Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis