The main idea of dual-FOFE is that it allows to use two different forgetting factors so that it can avoid the trade-off in choosing either a small or large values for the single forgetting factor.
The results on the challenging Google Billion word corpus show that both FOFE and dual FOFE yield very strong performance while significantly reducing the ...
The FOFE NNLM is a feed-forward model in which variable-length input sequences are encoded by fixed-size vectors, with minimal information loss.
Experimental results have shown that without using any recurrent feedbacks, FOFE based FNNLMs can significantly outperform not only the standard fixed-input ...
Duration: 12:47
Posted: Dec 13, 2018
Posted: Dec 13, 2018
The main idea behind dual-FOFE is that it allows the encoding to be done with two different forgetting factors; this would resolve the original FOFEs dilemma in ...
Missing: Competitive | Show results with:Competitive
Dual fixed-size ordinally forgetting encoding (fofe) for competitive neural language models. S Watcharawittayakul, M Xu, H Jiang. Proceedings of the 2018 ...
Jul 30, 2019 · This paper presents a simple and computationally efficient approach for entity linking (EL), compared with recurrent neural networks (RNNs) or convolutional ...
Dual Fixed-Size Ordinally Forgetting Encoding (FOFE) for Competitive Neural Language Models. Sedtawut Watcharawittayakul | Mingbin Xu | Hui Jiang | ...
Jul 30, 2019 · Abstract. This paper presents a simple and computationally efficient approach for entity linking (EL), compared with recurrent neural net-.