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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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1 result for “FloatSD8”
Low-Complexity LSTM Training and Inference with FloatSD8 Weight Representationcs.LG

Paper applies FloatSD8 to LSTM networks, reducing complexity and power.

problem Training and inference complexity of LSTM networks.
method Applied FloatSD8 for weights, 8-bit quantization for gradients/activations, reduced arithmetic precision.
result Successfully trained LSTM models with reduced complexity and preserved accuracy.
LSTMFloatSD8Recurrent Neural NetworksQuantizationTraining Complexity
2020-01-23abs ↗pdf ↗