Hierarchical Recurrent Neural Networks (HRNN) is an important advance in improving efficiency and performance of sequence classification in recent years.
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Hierarchical Recurrent Neural Networks (HRNN) is an important advance in improving efficiency and performance of sequence classification in recent years.
Sliding Hierarchical Recurrent Neural Networks for Sequence Classification
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The intuition behind this approach is to slice long sequences into many short sub-sequences and process them in parallel, then capturing the long-term.
Nov 30, 2023 · In this paper, we propose a gated linear RNN model dubbed Hierarchically Gated Recurrent Neural Network (HGRN), which includes forget gates that are lower ...
Missing: Sliding | Show results with:Sliding
Nov 8, 2023 · This allows the upper layers to model long-term dependencies and the lower layers to model more local, short-term dependencies. Experiments on ...
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Nov 8, 2023 · In this paper, we propose a gated linear RNN model dubbed Hierarchically Gated Recurrent Neural Network (HGRN), which includes forget gates that are lower ...
Missing: Sliding | Show results with:Sliding
Jul 27, 2017 · Methods: · Combines the previous cell state with the input. · Creates a new output · Updates the hidden state after passing the previous cell state ...
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In this work, we present a hierarchical neural network model for the sequential sentence classi- fication task, which we call a hierarchical sequen- tial ...
In this paper, we propose a novel multiscale approach, called the hierarchical multiscale recurrent neural network, that can capture the latent hierarchical ...