research
∙
04/04/2022
Soft Threshold Ternary Networks
Large neural networks are difficult to deploy on mobile devices because ...
share
research
∙
03/07/2022
Differentially Private Federated Learning with Local Regularization and Sparsification
User-level differential privacy (DP) provides certifiable privacy guaran...
research
∙
01/19/2022
Q-ViT: Fully Differentiable Quantization for Vision Transformer
In this paper, we propose a fully differentiable quantization method for...
research
∙
10/16/2021
DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy
Training deep neural networks (DNNs) for meaningful differential privacy...
research
∙
10/13/2021
Towards Mixed-Precision Quantization of Neural Networks via Constrained Optimization
Quantization is a widely used technique to compress and accelerate deep ...
research
∙
10/12/2021
Improving Binary Neural Networks through Fully Utilizing Latent Weights
Binary Neural Networks (BNNs) rely on a real-valued auxiliary variable W...
research
∙
01/21/2021
Generative Zero-shot Network Quantization
Convolutional neural networks are able to learn realistic image priors f...
research
∙
11/13/2019
Location-aware Upsampling for Semantic Segmentation
Many successful learning targets such as dice loss and cross-entropy los...
research
∙
10/19/2019
SpatialFlow: Bridging All Tasks for Panoptic Segmentation
The newly proposed panoptic segmentation task, which aims to encompass t...
research
∙
09/24/2019
A System-Level Solution for Low-Power Object Detection
Object detection has made impressive progress in recent years with the h...
research
∙
07/23/2019
Compact Global Descriptor for Neural Networks
Long-range dependencies modeling, widely used in capturing spatiotempora...
research
∙
02/08/2018
From Hashing to CNNs: Training BinaryWeight Networks via Hashing
Deep convolutional neural networks (CNNs) have shown appealing performan...
research
∙
02/03/2018
Recent Advances in Efficient Computation of Deep Convolutional Neural Networks
Deep neural networks have evolved remarkably over the past few years and...
research
∙
02/03/2018
A Survey on Acceleration of Deep Convolutional Neural Networks
Deep Neural Networks have achieved remarkable progress during the past f...
research
∙
11/07/2016
