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NN
2006
Springer
114views Neural Networks» more  NN 2006»
15 years 1 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
CIMCA
2008
IEEE
15 years 8 months ago
Seller's Strategies for Predicting Winning Bid Prices in Online Auctions
Online auctions have become extremely popular in recent years. Ability to predict winning bid prices accurately can help bidders to maximize their profit. This paper proposes a nu...
Yevgeniya Kovalchuk
FLAIRS
2001
15 years 3 months ago
Structural Learning in Object Oriented Domains
When constructing a Bayesian network, it can be advantageous to employ structural learning algorithms to combine knowledge captured in databases with prior information provided by...
Olav Bangsø, Helge Langseth, Thomas D. Niel...
166
Voted
CISIS
2011
IEEE
14 years 1 months ago
Improving Scheduling Techniques in Heterogeneous Systems with Dynamic, On-Line Optimisations
—Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive ap...
Marcin Bogdanski, Peter R. Lewis, Tobias Becker, X...
127
Voted
CVPR
1997
IEEE
16 years 3 months ago
Global Training of Document Processing Systems Using Graph Transformer Networks
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
Léon Bottou, Yoshua Bengio, Yann LeCun