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IPPS
1998
IEEE
13 years 11 months ago
Random Sampling Techniques in Parallel Computation
Abstract. Random sampling is an important tool in the design of parallel algorithms. Using random sampling it is possible to obtain simple parallel algorithms which are e cient in ...
Rajeev Raman
INFORMATICALT
2000
104views more  INFORMATICALT 2000»
13 years 7 months ago
Nonlinear Stochastic Optimization by the Monte-Carlo Method
Methods for solving stochastic optimization problems by Monte-Carlo simulation are considered. The stoping and accuracy of the solutions is treated in a statistical manner, testing...
Leonidas Sakalauskas
TIP
2002
109views more  TIP 2002»
13 years 7 months ago
Color plane interpolation using alternating projections
Most commercial digital cameras use color filter arrays to sample red, green, and blue colors according to a specific pattern. At the location of each pixel only one color sample i...
Bahadir K. Gunturk, Yucel Altunbasak, Russell M. M...
PAMI
2010
146views more  PAMI 2010»
13 years 5 months ago
A Generalized Kernel Consensus-Based Robust Estimator
In this paper, we present a new Adaptive Scale Kernel Consensus (ASKC) robust estimator as a generalization of the popular and state-of-the-art robust estimators such as RANSAC (R...
Hanzi Wang, Daniel Mirota, Gregory D. Hager
NN
2010
Springer
187views Neural Networks» more  NN 2010»
13 years 2 months ago
Efficient exploration through active learning for value function approximation in reinforcement learning
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiya...