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Found 5 papers, 2 papers with code
Adaptive Step Sizes for Preconditioned Stochastic Gradient Descent
Our framework enables the potential inclusion of a preconditioner, thereby enabling the implementation of adaptive step sizes for stochastic second-order optimization methods.
Sensitivity-Based Layer Insertion for Residual and Feedforward Neural Networks
The training of neural networks requires tedious and often manual tuning of the network architecture.
Frobenius-Type Norms and Inner Products of Matrices and Linear Maps with Applications to Neural Network Training
The Frobenius norm is a frequent choice of norm for matrices.
A primal dual projection algorithm for efficient constraint preconditioning
We consider a linear iterative solver for large scale linearly constrained quadratic minimization problems that arise, for example, in optimization with PDEs.
Optimization and Control Numerical Analysis Numerical Analysis 65F10, 35Q93, 35Q93
Optimal control of elliptic equations with positive measures
Optimal control problems without control costs in general do not possess solutions due to the lack of coercivity.
Optimization and Control
