Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Shen, Gehui"'
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 continual learning is very challenging, but it is closer to the real-worl
Externí odkaz:
http://arxiv.org/abs/2205.09347
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 acquisition of new knowledge. It is common to see previous experience get ov
Externí odkaz:
http://arxiv.org/abs/2006.05882
The ability of intelligent agents to learn and remember multiple tasks sequentially is crucial to achieving artificial general intelligence. Many continual learning (CL) methods have been proposed to overcome catastrophic forgetting which results fro
Externí odkaz:
http://arxiv.org/abs/2005.03490
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. However, RNNs generally read the whole text from beginning to end or v
Externí odkaz:
http://arxiv.org/abs/1905.11558
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 sentence representation for a variety of NLP tasks. However, RecNN is bor
Externí odkaz:
http://arxiv.org/abs/1808.06075
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 processing and transmission between adjacent RNNs' units. The proposed framew
Externí odkaz:
http://arxiv.org/abs/1806.00628
Most previous approaches to Chinese word segmentation can be roughly classified into character-based and word-based methods. The former regards this task as a sequence-labeling problem, while the latter directly segments character sequence into words
Externí odkaz:
http://arxiv.org/abs/1712.09509
Publikováno v:
In Neurocomputing 14 March 2021 429:69-76
Publikováno v:
In Neurocomputing 22 February 2021 426:227-234
Publikováno v:
In Expert Systems With Applications 1 March 2020 141