Pages that link to "Item:Q470178"

The following pages link to Batch gradient method with smoothing \(L_{1/2}\) regularization for training of feedforward neural networks (Q470178):

Displaying 8 items.

• Modeling of complex dynamic systems using differential neural networks with the incorporation of a priori knowledge (Q669392) (← links)
• Convergence analysis of an augmented algorithm for fully complex-valued neural networks (Q1669147) (← links)
• Convergence analysis of the batch gradient-based neuro-fuzzy learning algorithm with smoothing \(L_{1/2}\) regularization for the first-order Takagi-Sugeno system (Q1697505) (← links)
• Deterministic convergence analysis via smoothing group Lasso regularization and adaptive momentum for Sigma-Pi-Sigma neural network (Q2123539) (← links)
• The convergence analysis of spikeprop algorithm with smoothing \(L_{1/2}\) regularization (Q2179832) (← links)
• Convergence analyses on sparse feedforward neural networks via group lasso regularization (Q2292940) (← links)
• Convergence analysis for sigma-pi-sigma neural network based on some relaxed conditions (Q6149503) (← links)
• A backpropagation learning algorithm with graph regularization for feedforward neural networks (Q6195182) (← links)