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» Parameterized Complexity and Approximation Algorithms
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ICML
2009
IEEE
16 years 3 months ago
Robot trajectory optimization using approximate inference
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Marc Toussaint
136
Voted
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
SIGECOM
2010
ACM
184views ECommerce» more  SIGECOM 2010»
15 years 7 months ago
Computing pure strategy nash equilibria in compact symmetric games
We analyze the complexity of computing pure strategy Nash equilibria (PSNE) in symmetric games with a fixed number of actions. We restrict ourselves to “compact” representati...
Christopher Thomas Ryan, Albert Xin Jiang, Kevin L...
GRAPHICSINTERFACE
2007
15 years 4 months ago
Surface distance maps
We present an interactive algorithm to compute surface distance maps for triangulated models. The distance map represents the distance-to-closest-primitive mapping at each point o...
Avneesh Sud, Naga K. Govindaraju, Russell Gayle, E...
SIGGRAPH
2000
ACM
15 years 7 months ago
Dynamically reparameterized light fields
This research further develops the light field and lumigraph imagebased rendering methods and extends their utility. We present alternate parameterizations that permit 1) interac...
Aaron Isaksen, Leonard McMillan, Steven J. Gortler