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191
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HIS
2007
15 years 8 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
192
Voted
CIDR
2003
106views Algorithms» more  CIDR 2003»
15 years 8 months ago
Speculative Query Processing
Speculation is an every day phenomenon whereby one acts in anticipation of particular conditions that are likely to hold in the future. Computer science research has seen many suc...
Neoklis Polyzotis, Yannis E. Ioannidis
177
Voted
NIPS
1998
15 years 8 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
215
Voted
CEC
2010
IEEE
15 years 8 months ago
An analysis of massively distributed evolutionary algorithms
Computational science is placing new demands on optimization algorithms as the size of data sets and the computational complexity of scientific models continue to increase. As thes...
Travis J. Desell, David P. Anderson, Malik Magdon-...
212
Voted
ICA
2010
Springer
15 years 8 months ago
Binary Sparse Coding
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
Marc Henniges, Gervasio Puertas, Jörg Bornsch...
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