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Found 5 papers, 1 papers with code
Sleep Model -- A Sequence Model for Predicting the Next Sleep Stage
As sleep disorders are becoming more prevalent there is an urgent need to classify sleep stages in a less disturbing way. In particular, sleep-stage classification using simple sensors, such as single-channel electroencephalography (EEG), electrooculography (EOG), electromyography (EMG), or electrocardiography (ECG) has gained substantial interest.
Layer-wise Pruning of Transformer Attention Heads for Efficient Language Modeling
While Transformer-based models have shown impressive language modeling performance, the large computation cost is often prohibitive for practical use.
S-SGD: Symmetrical Stochastic Gradient Descent with Weight Noise Injection for Reaching Flat Minima
The proposed method is compared with the conventional SGD method and previous weight-noise injection algorithms using convolutional neural networks for image classification.
Fully Neural Network Based Speech Recognition on Mobile and Embedded Devices
The RNN implementation on embedded devices can suffer from excessive DRAM accesses because the parameter size of a neural network usually exceeds that of the cache memory and the parameters are used only once for each time step.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks
The approximate probability of each word can be estimated with only a small part of the weight matrix by using a few large singular values and the corresponding elements for most of the words.
