
ReLU Network Approximation in Terms of Intrinsic Parameters
This paper studies the approximation error of ReLU networks in terms of ...
read it

Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons
This paper develops simple feedforward neural networks that achieve the...
read it

Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
This paper concentrates on the approximation power of deep feedforward ...
read it

Neural Network Approximation: Three Hidden Layers Are Enough
A threehiddenlayer neural network with super approximation power is in...
read it

Deep Network Approximation with Discrepancy Being Reciprocal of Width to Power of Depth
A new network with super approximation power is introduced. This network...
read it

Optimization in Machine Learning: A Distribution Space Approach
We present the viewpoint that optimization problems encountered in machi...
read it

Deep Network Approximation for Smooth Functions
This paper establishes optimal approximation error characterization of d...
read it

Deep Learning via Dynamical Systems: An Approximation Perspective
We build on the dynamical systems approach to deep learning, where deep ...
read it

Deep Network Approximation Characterized by Number of Neurons
This paper quantitatively characterizes the approximation power of deep ...
read it

Nonlinear Approximation via Compositions
We study the approximation efficiency of function compositions in nonlin...
read it

On the Convergence and Robustness of Batch Normalization
Despite its empirical success, the theoretical underpinnings of the stab...
read it

Image Restoration: A General Wavelet Frame Based Model and Its Asymptotic Analysis
Image restoration is one of the most important areas in imaging science....
read it

On Bspline framelets derived from the unitary extension principle
Spline wavelet tight frames of RonShen have been used widely in frame b...
read it
Zuowei Shen
is this you? claim profile