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» A Data Locality Optimizing Algorithm
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96
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NIPS
2007
15 years 4 months ago
Convex Clustering with Exemplar-Based Models
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
Danial Lashkari, Polina Golland
174
Voted
SIGIR
2011
ACM
14 years 5 months ago
Collaborative competitive filtering: learning recommender using context of user choice
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
128
Voted
ICPP
1994
IEEE
15 years 6 months ago
Optimizing IPC Performance for Shared-Memory Multiprocessors
We assert that in order to perform well, a shared-memory multiprocessorinter-process communication (IPC)facility mustavoid a) accessing any shared data, and b) acquiring any locks...
Benjamin Gamsa, Orran Krieger, Michael Stumm
122
Voted
CORR
2007
Springer
95views Education» more  CORR 2007»
15 years 2 months ago
Scheduling in Data Intensive and Network Aware (DIANA) Grid Environments
In Grids scheduling decisions are often made on the basis of jobs being either data or computation intensive: in data intensive situations jobs may be pushed to the data and in co...
Richard McClatchey, Ashiq Anjum, Heinz Stockinger,...
106
Voted
IJCAI
2003
15 years 4 months ago
Distributed Clustering Based on Sampling Local Density Estimates
Huge amounts of data are stored in autonomous, geographically distributed sources. The discovery of previously unknown, implicit and valuable knowledge is a key aspect of the expl...
Matthias Klusch, Stefano Lodi, Gianluca Moro