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» The Tradeoffs of Large Scale Learning
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CORR
2010
Springer
153views Education» more  CORR 2010»
13 years 8 months ago
GraphLab: A New Framework for Parallel Machine Learning
Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insuf...
Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny B...
JMLR
2006
103views more  JMLR 2006»
13 years 7 months ago
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
Dana Pe'er, Amos Tanay, Aviv Regev
CVPR
2012
IEEE
11 years 10 months ago
Adaptive object tracking by learning background context
One challenge when tracking objects is to adapt the object representation depending on the scene context to account for changes in illumination, coloring, scaling, etc. Here, we p...
Ali Borji, Simone Frintrop, Dicky N. Sihite, Laure...
EPIA
2009
Springer
14 years 2 months ago
Learning Visual Object Categories with Global Descriptors and Local Features
Different types of visual object categories can be found in real-world applications. Some categories are very heterogeneous in terms of local features (broad categories) while oth...
Rui Pereira, Luís Seabra Lopes
IJCAI
2003
13 years 9 months ago
Learning Value Predictors for the Speculative Execution of Information Gathering Plans
Speculative execution of information gathering plans can dramatically reduce the effect of source I/O latencies on overall performance. However, the utility of speculation is clos...
Greg Barish, Craig A. Knoblock