4 papers
cs.LG2019
PowerNet: Efficient Representations of Polynomials and Smooth Functions by Deep Neural Networks with Rectified Power Units
Bo Li, Shanshan Tang, Haijun Yu
Deep neural network with rectified linear units (ReLU) is getting more and more popular recently. However, the derivatives of the function represented by a ReLU network are not con…
math.NA2019
Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units
Bo Li, Shanshan Tang, Haijun Yu
Deep neural networks with rectified linear units (ReLU) are getting more and more popular due to their universal representation power and successful applications. Some theoretical…
math.AP2016
Dual morse index estimates and application to Hamiltonian systems with P-boundary conditions
Shanshan Tang
In this paper, we study the multiplicity of Hamiltonian systems with P-boundary conditions.
math.AP2016
Minimal -symmetric periodic solutions of nonlinear Hamiltonian systems
Shanshan Tang
In this paper some existence results for the minimal P-symmetric periodic solutions are proved for first order autonomous Hamiltonian systems when the Hamiltonian function is super…