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ORL
1998
68views more  ORL 1998»
14 years 11 months ago
A fast bipartite network flow algorithm for selective assembly
Bipartite network flow problems naturally arise in applications such as selective assembly and preemptive scheduling. This paper presents fast algorithms for these problems that ...
Satoru Iwata, Tomomi Matsui, S. Thomas McCormick
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 11 days ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
IPSN
2010
Springer
15 years 6 months ago
Online distributed sensor selection
A key problem in sensor networks is to decide which sensors to query when, in order to obtain the most useful information (e.g., for performing accurate prediction), subject to co...
Daniel Golovin, Matthew Faulkner, Andreas Krause
PRL
2010
159views more  PRL 2010»
14 years 10 months ago
Creating diverse nearest-neighbour ensembles using simultaneous metaheuristic feature selection
The nearest-neighbour (1NN) classifier has long been used in pattern recognition, exploratory data analysis, and data mining problems. A vital consideration in obtaining good res...
Muhammad Atif Tahir, Jim E. Smith
ICDE
2001
IEEE
149views Database» more  ICDE 2001»
16 years 1 months ago
Selectivity Estimation for Spatial Joins
Spatial Joins are important and time consuming operations in spatial database management systems. It is crucial to be able to accurately estimate the performance of these operatio...
Ning An, Zhen-Yu Yang, Anand Sivasubramaniam