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» A New Migration Model For Distributed Genetic Algorithms
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MOR
2007
149views more  MOR 2007»
13 years 7 months ago
LP Rounding Approximation Algorithms for Stochastic Network Design
Real-world networks often need to be designed under uncertainty, with only partial information and predictions of demand available at the outset of the design process. The field ...
Anupam Gupta, R. Ravi, Amitabh Sinha
CORR
2007
Springer
169views Education» more  CORR 2007»
13 years 8 months ago
Algorithmic Complexity Bounds on Future Prediction Errors
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true d...
Alexey V. Chernov, Marcus Hutter, Jürgen Schm...
ICML
2008
IEEE
14 years 8 months ago
Training restricted Boltzmann machines using approximations to the likelihood gradient
A new algorithm for training Restricted Boltzmann Machines is introduced. The algorithm, named Persistent Contrastive Divergence, is different from the standard Contrastive Diverg...
Tijmen Tieleman
GECCO
2007
Springer
211views Optimization» more  GECCO 2007»
14 years 2 months ago
Multi-objective univariate marginal distribution optimisation of mixed analogue-digital signal circuits
Design for specific customer service plays a crucial role for the majority of the market in modern electronics. However, adaptability to an individual customer results in increasi...
Lyudmila Zinchenko, Matthias Radecker, Fabio Bisog...
INFOCOM
2007
IEEE
14 years 2 months ago
Performance Evaluation of Loss Networks via Factor Graphs and the Sum-Product Algorithm
— Loss networks provide a powerful tool for the analysis and design of many communication and networking systems. It is well known that a large number of loss networks have produ...
Jian Ni, Sekhar Tatikonda