no code implementations • 17 Jan 2024 • Ye Qiao, Haocheng Xu, Yifan Zhang, Sitao Huang
Neural Architecture Search (NAS) effectively discovers new Convolutional Neural Network (CNN) architectures, particularly for accuracy optimization.
no code implementations • 27 Jun 2023 • Yifan Zhang, Arnav Vaibhav Malawade, Xiaofang Zhang, Yuhui Li, DongHwan Seong, Mohammad Abdullah Al Faruque, Sitao Huang
Autonomous systems (AS) are systems that can adapt and change their behavior in response to unanticipated events and include systems such as aerial drones, autonomous vehicles, and ground/aquatic robots.
1 code implementation • 11 Apr 2023 • Junyao Wang, Sitao Huang, Mohsen Imani
Brain-inspired hyperdimensional computing (HDC) has been recently considered a promising learning approach for resource-constrained devices.
no code implementations • 11 Apr 2023 • Junyao Wang, Hanning Chen, Mariam Issa, Sitao Huang, Mohsen Imani
Cybersecurity has emerged as a critical challenge for the industry.
no code implementations • 16 Jan 2023 • Kun Wu, Mert Hidayetoğlu, Xiang Song, Sitao Huang, Da Zheng, Israt Nisa, Wen-mei Hwu
Relational graph neural networks (RGNNs) are graph neural networks with dedicated structures for modeling the different types of nodes and edges in heterogeneous graphs.
no code implementations • 3 Jul 2022 • Mang Yu, Sitao Huang, Deming Chen
However, with the high flexibility comes the difficulty in design and optimization.
no code implementations • 6 Jun 2022 • Xiaofan Zhang, Yao Chen, Cong Hao, Sitao Huang, Yuhong Li, Deming Chen
Deep Neural Networks (DNNs) have achieved great success in a variety of machine learning (ML) applications, delivering high-quality inferencing solutions in computer vision, natural language processing, and virtual reality, etc.
1 code implementation • 4 Mar 2021 • Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoğlu, JinJun Xiong, Eiman Ebrahimi, Deming Chen, Wen-mei Hwu
In this work, we propose a novel GPU-oriented data communication approach for GCN training, where GPU threads directly access sparse features in host memory through zero-copy accesses without much CPU help.
1 code implementation • 2 Mar 2021 • Kartik Hegde, Po-An Tsai, Sitao Huang, Vikas Chandra, Angshuman Parashar, Christopher W. Fletcher
The key idea is to derive a smooth, differentiable approximation to the otherwise non-smooth, non-convex search space.
1 code implementation • 20 Jan 2021 • Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoğlu, JinJun Xiong, Eiman Ebrahimi, Deming Chen, Wen-mei Hwu
While this process accounts for a significant portion of the training time, we find existing GNN implementations using popular deep neural network (DNN) libraries such as PyTorch are limited to a CPU-centric approach for the entire data preparation step.
2 code implementations • 9 Apr 2019 • Cong Hao, Xiaofan Zhang, Yuhong Li, Sitao Huang, JinJun Xiong, Kyle Rupnow, Wen-mei Hwu, Deming Chen
While embedded FPGAs are attractive platforms for DNN acceleration on edge-devices due to their low latency and high energy efficiency, the scarcity of resources of edge-scale FPGA devices also makes it challenging for DNN deployment.
4 code implementations • ICLR 2018 • Po-Sen Huang, Chong Wang, Sitao Huang, Dengyong Zhou, Li Deng
In this paper, we present Neural Phrase-based Machine Translation (NPMT).
Ranked #7 on Machine Translation on IWSLT2015 English-German