883 citations · 2.5k across the 44 of their papers we have counts for
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Automatically Evolving CNN Architectures Based on Blocks
Yanan Sun, Bing Xue, Mengjie Zhang +1
The performance of Convolutional Neural Networks (CNNs) highly relies on their architectures. In order to design a CNN with promising performance, extended expertise in both CNNs a…
Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy Regularization
Gang Chen, Yiming Peng, Mengjie Zhang
Recently deep reinforcement learning (DRL) has achieved outstanding success on solving many difficult and large-scale RL problems. However the high sample cost required for effecti…
A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification
Bin Wang, Yanan Sun, Bing Xue +1
Convolutional Neural Networks (CNNs) have demonstrated their superiority in image classification, and evolutionary computation (EC) methods have recently been surging to automatica…
Automatically designing CNN architectures using genetic algorithm for image classification
Yanan Sun, Bing Xue, Mengjie Zhang +1
Convolutional Neural Networks (CNNs) have gained a remarkable success on many image classification tasks in recent years. However, the performance of CNNs highly relies upon their…
An Adaptive Clipping Approach for Proximal Policy Optimization
Gang Chen, Yiming Peng, Mengjie Zhang
Very recently proximal policy optimization (PPO) algorithms have been proposed as first-order optimization methods for effective reinforcement learning. While PPO is inspired by th…
Evolving Deep Convolutional Neural Networks by Variable-length Particle Swarm Optimization for Image Classification
Bin Wang, Yanan Sun, Bing Xue +1
Convolutional neural networks (CNNs) are one of the most effective deep learning methods to solve image classification problems, but the best architecture of a CNN to solve a speci…