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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 5 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
TROB
2011
255views more  TROB 2011»
13 years 2 months ago
Active 3D Object Localization Using a Humanoid Robot
—We study the problem of actively searching for an object in a 3D environment under the constraint of a maximum search time, using a visually guided humanoid robot with twentysix...
Alexander Andreopoulos, Stephan Hasler, Heiko Wers...
JCS
2010
80views more  JCS 2010»
13 years 2 months ago
Constraint differentiation: Search-space reduction for the constraint-based analysis of security protocols
We introduce constraint differentiation, a powerful technique for reducing search when model-checking security protocols using constraint-based methods. Constraint differentiation...
Sebastian Mödersheim, Luca Viganò, Dav...
SIAMIS
2010
190views more  SIAMIS 2010»
13 years 2 months ago
Analysis and Generalizations of the Linearized Bregman Method
This paper analyzes and improves the linearized Bregman method for solving the basis pursuit and related sparse optimization problems. The analysis shows that the linearized Bregma...
Wotao Yin
LPAR
2012
Springer
12 years 3 months ago
E-Matching with Free Variables
E-matching is the most commonly used technique to handle quantifiers in SMT solvers. It works by identifying characteristic subexpressions of quantified formulae, named triggers,...
Philipp Rümmer