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NIPS
1994
15 years 7 months ago
Generalization in Reinforcement Learning: Safely Approximating the Value Function
To appear in: G. Tesauro, D. S. Touretzky and T. K. Leen, eds., Advances in Neural Information Processing Systems 7, MIT Press, Cambridge MA, 1995. A straightforward approach to t...
Justin A. Boyan, Andrew W. Moore
ICASSP
2010
IEEE
15 years 6 months ago
Symmetrical EEG/FMRI fusion with spatially adaptive priors using variational distribution approximation
In this paper, we propose a symmetrical EEG/fMRI fusion algorithm which combines EEG and fMRI by means of a common generative model. The use of a total variation (TV) prior as wel...
Martin Luessi, S. Derin Babacan, Rafael Molina, Ja...
EMNLP
2010
15 years 4 months ago
Turbo Parsers: Dependency Parsing by Approximate Variational Inference
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
André F. T. Martins, Noah A. Smith, Eric P....
ICASSP
2011
IEEE
14 years 10 months ago
Compressive sampling with a successive approximation ADC architecture
This paper proposes a compressive sampling scheme based on random temporal sampling using a successive approximation register (SAR) ADC architecture. Variable wordlength data samp...
Chenchi Luo, James H. McClellan
ICASSP
2011
IEEE
14 years 10 months ago
Approximation of pattern transformation manifolds with parametric dictionaries
The construction of low-dimensional models explaining highdimensional signal observations provides concise and efficient data representations. In this paper, we focus on pattern ...
Elif Vural, Pascal Frossard