Saliency-guided training combined with PACT quantization keeps MNIST and CIFAR-10 accuracy near parity with a quantized baseline, while the claimed efficiency and interpretability gains are not directly measured.
Owl: A General-Purpose Numerical Library in OCaml
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Owl is a new numerical library developed in the OCaml language. It focuses on providing a comprehensive set of high-level numerical functions so that developers can quickly build up data analytical applications. In this abstract, we will present Owl's design, core components, and its key functionality.
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Quantized and Interpretable Learning Scheme for Deep Neural Networks in Classification Task
Saliency-guided training combined with PACT quantization keeps MNIST and CIFAR-10 accuracy near parity with a quantized baseline, while the claimed efficiency and interpretability gains are not directly measured.