research
∙
09/22/2022
Nesting Forward Automatic Differentiation for Memory-Efficient Deep Neural Network Training
An activation function is an element-wise mathematical function and play...
share
research
∙
08/25/2022
Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization
Post-training quantization (PTQ) attracts increasing attention due to it...
research
∙
02/14/2022
SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Quantization of deep neural networks (DNN) has been proven effective for...
research
∙
08/29/2020
Accelerating Sparse DNN Models without Hardware-Support via Tile-Wise Sparsity
Network pruning can reduce the high computation cost of deep neural netw...
research
∙
08/23/2020
Ptolemy: Architecture Support for Robust Deep Learning
Deep learning is vulnerable to adversarial attacks, where carefully-craf...
research
∙
04/17/2019