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Liang Lan

2 accepted papers

2021

Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters

AAAI 2021technical

Deep Convolutional Neural Networks (CNN) have been successfully applied to many real-life problems. However, the huge memory cost of deep CNN models poses a great challenge of deploying them on memory-constrained devices (e.g., mobile phones). One popular way to reduce the memory cost of deep CNN mo…

Cited by 9SourcePDFScholar
2021

Memory and Computation-Efficient Kernel SVM via Binary Embedding and Ternary Model Coefficients

AAAI 2021technical

Kernel approximation is widely used to scale up kernel SVM training and prediction. However, the memory and computation costs of kernel approximation models are still too large if we want to deploy them on memory-limited devices such as mobile phones, smart watches and IoT devices. To address this c…

Cited by 0SourcePDFScholar