47 citations · 88 across the 13 of their papers we have counts for
5 papers · 1 filter
Effective Medical Test Suggestions Using Deep Reinforcement Learning
Yang-En Chen, Kai-Fu Tang, Yu-Shao Peng +1
Effective medical test suggestions benefit both patients and physicians to conserve time and improve diagnosis accuracy. In this work, we show that an agent can learn to suggest ef…
G2R Bound: A Generalization Bound for Supervised Learning from GAN-Synthetic Data
Fu-Chieh Chang, Hao-Jen Wang, Chun-Nan Chou +1
Performing supervised learning from the data synthesized by using Generative Adversarial Networks (GANs), dubbed GAN-synthetic data, has two important applications. First, GANs may…
MBS: Macroblock Scaling for CNN Model Reduction
Yu-Hsun Lin, Chun-Nan Chou, Edward Y. Chang
In this paper we propose the macroblock scaling (MBS) algorithm, which can be applied to various CNN architectures to reduce their model size. MBS adaptively reduces each CNN macro…
BRIEF: Backward Reduction of CNNs with Information Flow Analysis
Yu-Hsun Lin, Chun-Nan Chou, Edward Y. Chang
This paper proposes BRIEF, a backward reduction algorithm that explores compact CNN-model designs from the information flow perspective. This algorithm can remove substantial non-z…
EA-CG: An Approximate Second-Order Method for Training Fully-Connected Neural Networks
Sheng-Wei Chen, Chun-Nan Chou, Edward Y. Chang
For training fully-connected neural networks (FCNNs), we propose a practical approximate second-order method including: 1) an approximation of the Hessian matrix and 2) a conjugate…