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4. Ssgd: Sparsity-Promoting Stochastic Gradient Descent Algorithm For Unbiased Dnn Pruning

Ssgd: Sparsity-Promoting Stochastic Gradient Descent Algorithm For Unbiased Dnn Pruning

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IEEE ICASSP 2020 Virtual Conference May 2020

While deep neural networks (DNNs) have achieved state-of-the-art results in many fields, they are typically over-parameterized. Parameter redundancy, in turn, leads to inefficiency. Sparse signal recovery (SSR) techniques, on the other hand, find compact

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Ssgd: Sparsity-Promoting Stochastic Gradient Descent Algorithm For Unbiased Dnn Pruning

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While deep neural networks (DNNs) have achieved state-of-the-art results in many fields, they are typically over-parameterized. Parameter redundancy, in turn, leads to inefficiency. Sparse signal recovery (SSR) techniques, on the other hand, find compact