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117
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ALT
2006
Springer
16 years 18 days ago
Unsupervised Slow Subspace-Learning from Stationary Processes
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
Andreas Maurer
89
Voted
ICALT
2007
IEEE
15 years 5 months ago
Evaluating the automatic and manual creation process of adaptive lessons
Using adaptive, personalized courses is rewarding, as it can create a better learning experience, tailored for a specific learner’s needs. The process of creating these courses,...
Maurice Hendrix, Alexandra I. Cristea, Mike Joy
120
Voted
ICANN
2003
Springer
15 years 8 months ago
Online Processing of Multiple Inputs in a Sparsely-Connected Recurrent Neural Network
The storage and short-term memory capacities of recurrent neural networks of spiking neurons are investigated. We demonstrate that it is possible to process online many superimpose...
Julien Mayor, Wulfram Gerstner
97
Voted
CORR
2010
Springer
84views Education» more  CORR 2010»
15 years 3 months ago
Left-Inverses of Fractional Laplacian and Sparse Stochastic Processes
The fractional Laplacian (-)/2 commutes with the primary coordination transformations in the Euclidean space Rd: dilation, translation and rotation, and has tight link to splines, ...
Qiyu Sun, Michael Unser
132
Voted
ML
2002
ACM
143views Machine Learning» more  ML 2002»
15 years 3 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng