1 code implementation • 27 Oct 2022 • Zhiqi Shao, Andi Han, Dai Shi, Andrey Vasnev, Junbin Gao
This paper introduces a novel Framelet Graph approach based on p-Laplacian GNN.
no code implementations • 17 Aug 2020 • Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
In this study, we investigate learning rate adaption at different levels based on the hyper-gradient descent framework and propose a method that adaptively learns the optimizer parameters by combining multiple levels of learning rates with hierarchical structures.
no code implementations • 26 Jul 2020 • Renlong Jie, Junbin Gao, Andrey Vasnev, Min-ngoc Tran
Based on this, a novel family of flexible activation functions that can replace sigmoid or tanh in LSTM cells are implemented, as well as a new family by combining ReLU and ELUs.
no code implementations • 25 Sep 2019 • Renlong Jie, Junbin Gao, Andrey Vasnev, Minh-Ngoc Tran
Based on this, we develop two novel flexible activation functions that can be implemented in LSTM cells and auto-encoder layers.