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» Subexponential Parameterized Algorithms
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PPSN
1998
Springer
15 years 7 months ago
On Risky Methods for Local Selection under Noise
The choice of the selection method used in an evolutionary algorithm may have considerable impacts on the behavior of the entire algorithm. Therefore, earlier work was devoted to t...
Günter Rudolph
APPINF
2003
15 years 4 months ago
Debugging Distributed Computations by Reverse Search
We develop a memory-efficient off-line algorithm for the enumeration of global states of a distributed computation. The algorithm allows the parameterization of its memory requir...
Artur Andrzejak, Komei Fukuda
IJCAI
2003
15 years 4 months ago
Covariant Policy Search
We investigate the problem of non-covariant behavior of policy gradient reinforcement learning algorithms. The policy gradient approach is amenable to analysis by information geom...
J. Andrew Bagnell, Jeff G. Schneider
ICASSP
2011
IEEE
14 years 7 months ago
Natural gradient approach in orthogonal matrix optimization using cayley transform
Matrix optimization with orthogonal constraints appear in a variety of application fields including signal and image processing. Several researchers have developed algorithms for...
Gen Hori
NIPS
1998
15 years 4 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore