We’re releasing highly optimized GPU kernels for an underexplored class of neural network architectures: networks with block-sparse weights. The kernels allow for efficient evaluation and differentiation of linear layers, including convolutional layers, with flexibly configurable block-sparsity patterns in the weight matrix... (read more)
PDF AbstractTASK | DATASET | MODEL | METRIC NAME | METRIC VALUE | GLOBAL RANK | USES EXTRA TRAINING DATA |
BENCHMARK |
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Sentiment Analysis | CR | Block-sparse LSTM | Accuracy | 92.2 | # 1 | ||
Sentiment Analysis | IMDb | Block-sparse LSTM | Accuracy | 94.99 | # 10 | ||
Sentiment Analysis | SST-2 Binary classification | Block-sparse LSTM | Accuracy | 93.2 | # 23 | ||
Sentiment Analysis | Yelp Binary classification | Block-sparse LSTM | Error | 3.27 | # 10 |
METHOD | TYPE | |
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🤖 No Methods Found | Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet |