research
∙
09/23/2022
Faith: An Efficient Framework for Transformer Verification on GPUs
Transformer verification draws increasing attention in machine learning ...
share
research
∙
02/28/2022
Dynamic N:M Fine-grained Structured Sparse Attention Mechanism
Transformers are becoming the mainstream solutions for various tasks lik...
research
∙
10/21/2021
Transformer Acceleration with Dynamic Sparse Attention
Transformers are the mainstream of NLP applications and are becoming inc...
research
∙
07/25/2021
H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks
Although spiking neural networks (SNNs) take benefits from the bio-plaus...
research
∙
01/28/2020
Characterizing and Understanding GCNs on GPU
Graph convolutional neural networks (GCNs) have achieved state-of-the-ar...
research
∙
01/01/2020
A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks
In recent years, plenty of metrics have been proposed to identify networ...
research
∙
03/13/2019
Hardness-Aware Deep Metric Learning
This paper presents a hardness-aware deep metric learning (HDML) framewo...
research
∙
10/25/2018
