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SMC
2007
IEEE
125views Control Systems» more  SMC 2007»
14 years 3 months ago
A hierarchical strategy for learning of robot walking strategies in natural terrain environments
– In this paper, we present a hierarchical methodology that learns new walking gaits autonomously while operating in an uncharted environment, such as on the Mars planetary surfa...
Ayanna M. Howard, Lonnie T. Parker
ICLP
2010
Springer
14 years 1 months ago
Learning Domain-Specific Heuristics for Answer Set Solvers
In spite of the recent improvements in the performance of Answer Set Programming (ASP) solvers, when the search space is sufficiently large, it is still possible for the search al...
Marcello Balduccini
AAAI
2008
13 years 11 months ago
Bounding the False Discovery Rate in Local Bayesian Network Learning
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
Ioannis Tsamardinos, Laura E. Brown
IJCAI
2003
13 years 10 months ago
Spectral Learning
We present a simple, easily implemented spectral learning algorithm which applies equally whether we have no supervisory information, pairwise link constraints, or labeled example...
Sepandar D. Kamvar, Dan Klein, Christopher D. Mann...
AAAI
1997
13 years 10 months ago
Worst-Case Absolute Loss Bounds for Linear Learning Algorithms
The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrateworst-case upper bounds on the absolute loss for the perceptron algorithm and ...
Tom Bylander