Papers by Topics – Fundamental Machine Learning

• On Output Activation Functions for Adversarial Losses: A Theoretical Analysis via Variational Divergence Minimization and An Empirical Study on MNIST Classification
  Hao-Wen Dong and Yi-Hsuan Yang
  arXiv preprint arXiv:1901.08753, 2019
  paper  demo  code
  Fundamental Machine Learning

• Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation
  Hao-Wen Dong and Yi-Hsuan Yang
  arXiv preprint arXiv:1810.04714, 2018
  paper  demo  slides  code
  Fundamental Machine Learning