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» The Tradeoffs of Large Scale Learning
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ICPADS
2005
IEEE
14 years 1 months ago
Distributed Spanning Tree Algorithms for Large Scale Traversals
— The Distributed Spanning Tree (DST) is an overlay structure designed to be scalable. It supports the growth from small scale to large scale. The DST is a tree without bottlenec...
Sylvain Dahan
KDD
2008
ACM
128views Data Mining» more  KDD 2008»
14 years 8 months ago
Scaling up text classification for large file systems
: We combine the speed and scalability of information retrieval with the generally superior classification accuracy offered by machine learning, yielding a two-phase text classifie...
George Forman, Shyamsundar Rajaram
INFOCOM
2010
IEEE
13 years 6 months ago
UUSee: Large-Scale Operational On-Demand Streaming with Random Network Coding
—Since the inception of network coding in information theory, we have witnessed a sharp increase of research interest in its applications in communications and networking, where ...
Zimu Liu, Chuan Wu, Baochun Li, Shuqiao Zhao
ICDM
2009
IEEE
156views Data Mining» more  ICDM 2009»
13 years 5 months ago
Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging
We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal ...
CVPR
2008
IEEE
14 years 1 months ago
General Constraints for Batch Multiple-Target Tracking Applied to Large-Scale Videomicroscopy
While there is a large class of Multiple-Target Tracking (MTT) problems for which batch processing is possible and desirable, batch MTT remains relatively unexplored in comparis...
Kevin Smith, Alan Carleton, Vincent Lepetit