基於深度學習之低解析度文字辨識 - 政大學術集成

Wang, Solving pseudomonotone variational inequalities and pseudocon- vex optimization problems using the projection neural network, IEEE Transactions on Neural Networks 17

Wang (2006), Solving pseudomonotone variational inequalities and pseudoconvex optimization problems using the projection neural network, IEEE Trans- actions on Neural Networks,

For example, Ko, Chen and Yang [22] proposed two kinds of neural networks with different SOCCP functions for solving the second-order cone program; Sun, Chen and Ko [29] gave two

Wang, A recurrent neural network for solving nonlinear convex programs subject to linear constraints, IEEE Transactions on Neural Networks, vol..

In this paper, we build a new class of neural networks based on the smoothing method for NCP introduced by Haddou and Maheux [18] using some family F of smoothing functions.

SG is simple and effective, but sometimes not robust (e.g., selecting the learning rate may be difficult) Is it possible to consider other methods.. In this work, we investigate

{ Title: Using neural networks to forecast the systematic risk..

Ongoing Projects in Image/Video Analytics with Deep Convolutional Neural Networks. § Goal – Devise effective and efficient learning methods for scalable visual analytic