9 citations · 16 across the 4 of their papers we have counts for
7 papers
Bypassing Logits Bias in Online Class-Incremental Learning with a Generative Framework
Gehui Shen, Shibo Jie, Ziheng Li +1
Continual learning requires the model to maintain the learned knowledge while learning from a non-i.i.d data stream continually. Due to the single-pass training setting, online con…
Self-Supervised Learning Aided Class-Incremental Lifelong Learning
Song Zhang, Gehui Shen, Jinsong Huang +1
Lifelong or continual learning remains to be a challenge for artificial neural network, as it is required to be both stable for preservation of old knowledge and plastic for acquis…
Generative Feature Replay with Orthogonal Weight Modification for Continual Learning
Gehui Shen, Song Zhang, Xiang Chen +1
The ability of intelligent agents to learn and remember multiple tasks sequentially is crucial to achieving artificial general intelligence. Many continual learning (CL) methods ha…
Leap-LSTM: Enhancing Long Short-Term Memory for Text Categorization
Ting Huang, Gehui Shen, Zhi-Hong Deng
Recurrent Neural Networks (RNNs) are widely used in the field of natural language processing (NLP), ranging from text categorization to question answering and machine translation.…
Learning to Compose over Tree Structures via POS Tags
Gehui Shen, Zhi-Hong Deng, Ting Huang +1
Recursive Neural Network (RecNN), a type of models which compose words or phrases recursively over syntactic tree structures, has been proven to have superior ability to obtain sen…
A Novel Framework for Recurrent Neural Networks with Enhancing Information Processing and Transmission between Units
Xi Chen, Zhihong Deng, Gehui Shen +1
This paper proposes a novel framework for recurrent neural networks (RNNs) inspired by the human memory models in the field of cognitive neuroscience to enhance information process…