Pages that link to "Item:Q2156337"

The following pages link to Landscape analysis for shallow neural networks: complete classification of critical points for affine target functions (Q2156337):

Displaying 9 items.

• Critical points for least-squares problems involving certain analytic functions, with applications to sigmoidal nets (Q1923891) (← links)
• The global optimization geometry of shallow linear neural networks (Q1988338) (← links)
• Symmetry \& critical points for a model shallow neural network (Q2077613) (← links)
• Convergence analysis for gradient flows in the training of artificial neural networks with ReLU activation (Q2079548) (← links)
• A proof of convergence for stochastic gradient descent in the training of artificial neural networks with ReLU activation for constant target functions (Q2167333) (← links)
• Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity (Q5051381) (← links)
• Non-differentiable saddle points and sub-optimal local minima exist for deep ReLU networks (Q6055135) (← links)
• On the existence of minimizers in shallow residual ReLU neural network optimization landscapes (Q6652417) (← links)
• Gradient descent provably escapes saddle points in the training of shallow ReLU networks (Q6655804) (← links)