论文标题
凸功能的Groupmax神经网络近似
The GroupMax neural network approximation of convex functions
论文作者
论文摘要
我们提出了一个新的神经网络，以近似凸功能。该网络的特殊性可以通过切割近似函数，并且很容易适应部分凸度。我们在完整的凸情况下给出了通用近似定理，并给出许多数值结果证明其效率。
We present a new neural network to approximate convex functions. This network has the particularity to approximate the function with cuts and can be easily adapted to partial convexity. We give an universal approximation theorem in the full convex case and give many numerical results proving it efficiency.
