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cs.LG2021
Generating meta-learning tasks to evolve parametric loss for classification learning
Zhaoyang Hai, Xiabi Liu, Yuchen Ren +1
The field of meta-learning has seen a dramatic rise in interest in recent years. In existing meta-learning approaches, learning tasks for training meta-models are usually collected…
cs.LG2021
A Novel Structured Natural Gradient Descent for Deep Learning
Weihua Liu, Xiabi Liu
Natural gradient descent (NGD) provided deep insights and powerful tools to deep neural networks. However the computation of Fisher information matrix becomes more and more difficu…
cs.LG2021
Explore the Knowledge contained in Network Weights to Obtain Sparse Neural Networks
Mengqiao Han, Xiabi Liu, Zhaoyang Hai +1
Sparse neural networks are important for achieving better generalization and enhancing computation efficiency. This paper proposes a novel learning approach to obtain sparse fully…