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» Hardening Functions for Large Scale Distributed Computations
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VLSID
2007
IEEE
154views VLSI» more  VLSID 2007»
16 years 5 months ago
Application Specific Datapath Extension with Distributed I/O Functional Units
Performance of an application can be improved through augmenting the processor with Application specific Functional Units (AFUs). Usually a cluster of operations identified from th...
Nagaraju Pothineni, Anshul Kumar, Kolin Paul
CVPR
2009
IEEE
16 years 11 months ago
Active Learning for Large Multi-class Problems
Scarcity and infeasibility of human supervision for large scale multi-class classification problems necessitates active learning. Unfortunately, existing active learning methods ...
Prateek Jain (University of Texas at Austin), Ashi...
ICDCS
2005
IEEE
15 years 10 months ago
Comparison of Approaches to Service Deployment
IT today is driven by the trend of increasing scale and complexity. Utility and Grid computing models, PlanetLab, and traditional data centers, are reaching the scale of thousands...
Vanish Talwar, Qinyi Wu, Calton Pu, Wenchang Yan, ...
ECCV
2010
Springer
15 years 9 months ago
Learning a Fine Vocabulary
We present a novel similarity measure for bag-of-words type large scale image retrieval. The similarity function is learned in an unsupervised manner, requires no extra space over ...
EDBT
2009
ACM
175views Database» more  EDBT 2009»
15 years 11 months ago
Towards materialized view selection for distributed databases
Materialized views (MV) can significantly improve the query performance of relational databases. In this paper, we consider MVs to optimize complex scenarios where many heterogen...
Leonardo Weiss Ferreira Chaves, Erik Buchmann, Fab...