Affiliation:
1. Department of Artificial Intelligence, Inha University, Incheon, Republic of Korea
Funder
Inha University Research Grant
Institute of Information and Communications Technology Planning and Evaluation (IITP) Grant
Korea Government [Ministry of Science and ICT (MSIT)] [Artificial Intelligence Convergence Innovation Human Resources Development (Inha University)]
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Reference65 articles.
1. A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning
2. Learning sparse neural networks through L0 regularization;louizos;arXiv 1712 01312,2017
3. Categorical reparameterization with Gumbel-softmax;jang;Proc Int Conf Learn Represent (ICLR),2017
4. Variational dropout sparsifies deep neural networks;molchanov;Proc Int Conf Mach Learn,2017