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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.

169,181 papers · 148 categories

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3 results for TensorQuant

The paper investigates sparsity in deep neural networks, especially in larger models.

problem Reducing resource demands in deep neural networks, particularly in larger models.
method Extended TensorQuant toolbox to investigate sparsity in deeper models and various classification problem sizes.
result Promoted sparsity in deeper models, showing differences in sparsity for activations, weights, and gradients.

A new method reduces training time and improves accuracy in machine learning models.

problem The tradeoff between training accuracy and precision in low-precision machine learning.
method A low-precision stochastic gradient descent variant called HALP, using SVRG to reduce gradient variance and bit centering to reduce quantization error.
result HALP converges at the same theoretical rate as full-precision algorithms despite quantization noise.