9 citations · 22 across the 8 of their papers we have counts for
8 papers
MTLight: Efficient Multi-Task Reinforcement Learning for Traffic Signal Control
Liwen Zhu, Peixi Peng, Zongqing Lu +1
Traffic signal control has a great impact on alleviating traffic congestion in modern cities. Deep reinforcement learning (RL) has been widely used for this task in recent years, d…
Adaptive Discovering and Merging for Incremental Novel Class Discovery
Guangyao Chen, Peixi Peng, Yangru Huang +2
One important desideratum of lifelong learning aims to discover novel classes from unlabelled data in a continuous manner. The central challenge is twofold: discovering and learnin…
Fully Spiking Actor Network with Intra-layer Connections for Reinforcement Learning
Ding Chen, Peixi Peng, Tiejun Huang +1
With the help of special neuromorphic hardware, spiking neural networks (SNNs) are expected to realize artificial intelligence (AI) with less energy consumption. It provides a prom…
Learning Sparse Neural Networks with Identity Layers
Mingjian Ni, Guangyao Chen, Xiawu Zheng +3
The sparsity of Deep Neural Networks is well investigated to maximize the performance and reduce the size of overparameterized networks as possible. Existing methods focus on pruni…
Population-Based Evolutionary Gaming for Unsupervised Person Re-identification
Yunpeng Zhai, Peixi Peng, Mengxi Jia +4
Unsupervised person re-identification has achieved great success through the self-improvement of individual neural networks. However, limited by the lack of diversity of discrimina…
Picking Up Quantization Steps for Compressed Image Classification
Li Ma, Peixi Peng, Guangyao Chen +3
The sensitivity of deep neural networks to compressed images hinders their usage in many real applications, which means classification networks may fail just after taking a screens…