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Found 5 papers, 1 papers with code
Dependent Bidirectional RNN with Extended-long Short-term Memory
Based on the analysis, we propose a new design, called the extended-long short-term memory (ELSTM), to extend the memory length of a cell.
Efficient Text Classification Using Tree-structured Multi-linear Principal Component Analysis
A novel text data dimension reduction technique, called the tree-structured multi-linear principal component anal- ysis (TMPCA), is proposed in this work.
On Extended Long Short-term Memory and Dependent Bidirectional Recurrent Neural Network
In this work, we first analyze the memory behavior in three recurrent neural networks (RNN) cells; namely, the simple RNN (SRN), the long short-term memory (LSTM) and the gated recurrent unit (GRU), where the memory is defined as a function that maps previous elements in a sequence to the current output.
Tree-structured multi-stage principal component analysis (TMPCA): theory and applications
A PCA based sequence-to-vector (seq2vec) dimension reduction method for the text classification problem, called the tree-structured multi-stage principal component analysis (TMPCA) is presented in this paper.
Unsupervised Multi-modal Neural Machine Translation
Unsupervised neural machine translation (UNMT) has recently achieved remarkable results with only large monolingual corpora in each language.
