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» General Convergence Results for Linear Discriminant Updates
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TSP
2010
13 years 2 months ago
A subband adaptive iterative shrinkage/thresholding algorithm
We investigate a subband adaptive version of the popular iterative shrinkage/thresholding algorithm that takes different update steps and thresholds for each subband. In particular...
Ilker Bayram, Ivan W. Selesnick
ECML
2004
Springer
14 years 26 days ago
Convergence and Divergence in Standard and Averaging Reinforcement Learning
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
Marco Wiering
ICIP
1995
IEEE
14 years 9 months ago
Parallel computation of sequential pixel updates in statistical tomographic reconstruction
While Bayesian methods can significantly improve the quality of tomographic reconstructions, they require the solution of large iterative optimization problems. Recent results ind...
Ken D. Sauer, S. Borman, Charles A. Bouman
ICML
2004
IEEE
14 years 8 months ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht
PAMI
2011
13 years 2 months ago
Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
Hongping Cai, Krystian Mikolajczyk, Jiri Matas