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ICANN
2010
Springer
14 years 12 months ago
Dynamic Shape Learning and Forgetting
In this paper, we present a system capable of dynamically learning shapes in a way that also allows for the dynamic deletion of shapes already learned. It uses a self-balancing Bin...
Nikolaos Tsapanos, Anastasios Tefas, Ioannis Pitas
PLDI
2012
ACM
13 years 3 months ago
Speculative separation for privatization and reductions
Automatic parallelization is a promising strategy to improve application performance in the multicore era. However, common programming practices such as the reuse of data structur...
Nick P. Johnson, Hanjun Kim, Prakash Prabhu, Ayal ...
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
15 years 6 months ago
Parallel community detection on large networks with propinquity dynamics
Graphs or networks can be used to model complex systems. Detecting community structures from large network data is a classic and challenging task. In this paper, we propose a nove...
Yuzhou Zhang, Jianyong Wang, Yi Wang, Lizhu Zhou
ICML
2005
IEEE
16 years 2 months ago
Learning class-discriminative dynamic Bayesian networks
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
John Burge, Terran Lane
EDBT
2009
ACM
108views Database» more  EDBT 2009»
15 years 6 months ago
Reverse k-nearest neighbor search in dynamic and general metric databases
In this paper, we propose an original solution for the general reverse k-nearest neighbor (RkNN) search problem. Compared to the limitations of existing methods for the RkNN searc...
Elke Achtert, Hans-Peter Kriegel, Peer Kröger...