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» Hardening Functions for Large Scale Distributed Computations
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ECCV
2008
Springer
16 years 6 months ago
SERBoost: Semi-supervised Boosting with Expectation Regularization
The application of semi-supervised learning algorithms to large scale vision problems suffers from the bad scaling behavior of most methods. Based on the Expectation Regularization...
Amir Saffari, Helmut Grabner, Horst Bischof
194
Voted
MIR
2005
ACM
133views Multimedia» more  MIR 2005»
15 years 10 months ago
Probabilistic web image gathering
We propose a new method for automated large scale gathering of Web images relevant to specified concepts. Our main goal is to build a knowledge base associated with as many conce...
Keiji Yanai, Kobus Barnard
SOSP
2009
ACM
16 years 1 months ago
Distributed aggregation for data-parallel computing: interfaces and implementations
Data-intensive applications are increasingly designed to execute on large computing clusters. Grouped aggregation is a core primitive of many distributed programming models, and i...
Yuan Yu, Pradeep Kumar Gunda, Michael Isard
165
Voted
CCGRID
2011
IEEE
14 years 8 months ago
Towards Real-Time, Volunteer Distributed Computing
Many large-scale distributed computing applications demand real-time responses by soft deadlines. To enable such real-time task distribution and execution on the volunteer resourc...
Sangho Yi, Emmanuel Jeannot, Derrick Kondo, David ...
PVLDB
2008
103views more  PVLDB 2008»
15 years 4 months ago
A request-routing framework for SOA-based enterprise computing
Enterprises may use a service-oriented architecture (SOA) to provide a streamlined interface to their business processes. To scale up the system, each tier in a composite service ...
Thomas Phan, Wen-Syan Li