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132
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CORR
2010
Springer
153views Education» more  CORR 2010»
15 years 3 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...
272
Voted
DSP
2007
15 years 3 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...
103
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IJON
2007
117views more  IJON 2007»
15 years 3 months ago
Learning sensory representations with intrinsic plasticity
Intrinsic plasticity (IP) refers to a neuron’s ability to regulate its firing activity by adapting its intrinsic excitability. Previously, we showed that model neurons combinin...
Nicholas Butko, Jochen Triesch
112
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APIN
2005
107views more  APIN 2005»
15 years 3 months ago
Multi-Instance Learning Based Web Mining
In multi-instance learning, the training set comprises labeled bags that are composed of unlabeled instances, and the task is to predict the labels of unseen bags. In this paper, ...
Zhi-Hua Zhou, Kai Jiang, Ming Li
128
Voted
NN
2007
Springer
106views Neural Networks» more  NN 2007»
15 years 3 months ago
Machine learning approach to color constancy
A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (...
Vivek Agarwal, Andrei V. Gribok, Mongi A. Abidi