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» Distributed Data Clustering Can Be Efficient and Exact
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CCGRID
2008
IEEE
16 years 1 months ago
GridBatch: Cloud Computing for Large-Scale Data-Intensive Batch Applications
To be competitive, Enterprises are collecting and analyzing increasingly large amount of data in order to derive business insights. However, there are at least two challenges to m...
Huan Liu, Dan Orban
MM
2006
ACM
79views Multimedia» more  MM 2006»
16 years 16 days ago
ViCo: an adaptive distributed video correlation system
Many emerging applications such as video sensor monitoring can benefit from an on-line video correlation system, which can be used to discover linkages between different video s...
Xiaohui Gu, Zhen Wen, Ching-Yung Lin, Philip S. Yu
SSDBM
2006
IEEE
122views Database» more  SSDBM 2006»
16 years 17 days ago
Probabilistic Ranking Queries on Gaussians
In many modern applications, there are no exact values available to describe the data objects. Instead, the feature values are considered to be uncertain. This uncertainty is mode...
Christian Böhm, Alexey Pryakhin, Matthias Sch...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 7 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
STOC
2003
ACM
95views Algorithms» more  STOC 2003»
16 years 6 months ago
Random knapsack in expected polynomial time
In this paper, we present the first average-case analysis proving an expected polynomial running time for an exact algorithm for the 0/1 knapsack problem. In particular, we prove,...
René Beier, Berthold Vöcking