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» The Measurable Space of Stochastic Processes
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AAAI
1998
13 years 11 months ago
Solving Very Large Weakly Coupled Markov Decision Processes
We present a technique for computing approximately optimal solutions to stochastic resource allocation problems modeled as Markov decision processes (MDPs). We exploit two key pro...
Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, L...
GECCO
2005
Springer
122views Optimization» more  GECCO 2005»
14 years 3 months ago
An enhanced GA to improve the search process reliability in tuning of control systems
Evolutionary Algorithms (EAs) have been largely applied to optimisation and synthesis of controllers. In spite of several successful applications and competitive solutions, the st...
Andrea Soltoggio
PAMI
2010
238views more  PAMI 2010»
13 years 8 months ago
Tracking Motion, Deformation, and Texture Using Conditionally Gaussian Processes
—We present a generative model and inference algorithm for 3D nonrigid object tracking. The model, which we call G-flow, enables the joint inference of 3D position, orientation, ...
Tim K. Marks, John R. Hershey, Javier R. Movellan
ICASSP
2011
IEEE
13 years 1 months ago
Improving head-related impulse response measured in noisy environments with spatio-temporal frequency analysis
A new noise reduction method based on spatio-temporal frequency analysis is proposed that can be applied to head-related impulse response (HRIR), which is an impulse response betw...
Takanori Nishino, Kazuya Takeda
ECCB
2002
IEEE
14 years 2 months ago
Stochastic roadmap simulation for the study of ligand-protein interactions
The dynamics of ligand-protein interactions are necessary to understand for the design of novel therapeutic agents. In this paper, we establish the use of Stochastic Roadmap Simul...
Mehmet Serkan Apaydin, Carlos Guestrin, Chris Varm...