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Found 3 papers, 0 papers with code
Optimal Hyperparameter $ε$ for Adaptive Stochastic Optimizers through Gradient Histograms
In this manuscript, we introduce a new framework based on gradient histograms to analyze and justify important attributes of adaptive optimizers, such as their optimal performance and the relationships and dependencies among hyperparameters.
Efficient Consensus Model based on Proximal Gradient Method applied to Convolutional Sparse Problems
Convolutional sparse representation (CSR), shift-invariant model for inverse problems, has gained much attention in the fields of signal/image processing, machine learning and computer vision.
Convolutional Sparse Coding: Boundary Handling Revisited
Two different approaches have recently been proposed for boundary handling in convolutional sparse representations, avoiding potential boundary artifacts arising from the circular boundary conditions implied by the use of frequency domain solution methods by introducing a spatial mask into the convolutional sparse coding problem.
