12 citations · 13 across the 8 of their papers we have counts for
8 papers
Unconstrained optimization using the directional proximal point method
Ming-Yu Chung, Jinn Ho, Wen-Liang Hwang
This paper presents a directional proximal point method (DPPM) to derive the minimum of any C1-smooth function f. The proposed method requires a function persistent a local convex…
Learning DNN networks using un-rectifying ReLU with compressed sensing application
Wen-Liang Hwang, Shih-Shuo Tung
The un-rectifying technique expresses a non-linear point-wise activation function as a data-dependent variable, which means that the activation variable along with its input and ou…
Deep Representation with ReLU Neural Networks
Andreas Heinecke, Wen-Liang Hwang
We consider deep feedforward neural networks with rectified linear units from a signal processing perspective. In this view, such representations mark the transition from using a s…
Link Delay Estimation Using Sparse Recovery for Dynamic Network Tomography
Hao-Ting Wei, Sung-Hsien Hsieh, Wen-Liang Hwang +2
When the scale of communication networks has been growing rapidly in the past decades, it becomes a critical challenge to extract fast and accurate estimation of key state paramete…
Frame-based Sparse Analysis and Synthesis Signal Representations and Parseval K-SVD
Wen-Liang Hwang, Ping-Tzan Huang, Tai-Lang Jong
Frames are the foundation of the linear operators used in the decomposition and reconstruction of signals, such as the discrete Fourier transform, Gabor, wavelets, and curvelet tra…
A Theorem on Multi-Objective Optimization Approach for Bit Allocation of Scalable Coding
Wen-Liang Hwang
In the current work, we have formulated the optimal bit-allocation problem for a scalable codec of images or videos as a constrained vector-valued optimization problem and demonstr…
Frame-based Approach for Sparse Representation of Signal Decomposition and Reconstruction
Wen-Liang Hwang
Frame is the corner stone for designing decomposition and reconstruction operations in signal processing. Famous frames include wavelets, curvelets,and Gabor. A celebrated result i…
Sparse Representation of a Blur Kernel for Blind Image Restoration
Chia-Chen Lee, Wen-Liang Hwang
Blind image restoration is a non-convex problem which involves restoration of images from an unknown blur kernel. The factors affecting the performance of this restoration are how…