Search Results for author: Hongxin Hu

Found 8 papers, 4 papers with code

Understanding and Measuring Robustness of Multimodal Learning

no code implementations22 Dec 2021 Nishant Vishwamitra, Hongxin Hu, Ziming Zhao, Long Cheng, Feng Luo

We then introduce a new type of multimodal adversarial attacks called decoupling attack in MUROAN that aims to compromise multimodal models by decoupling their fused modalities.

Adversarial Robustness

CARTL: Cooperative Adversarially-Robust Transfer Learning

1 code implementation12 Jun 2021 Dian Chen, Hongxin Hu, Qian Wang, Yinli Li, Cong Wang, Chao Shen, Qi Li

In deep learning, a typical strategy for transfer learning is to freeze the early layers of a pre-trained model and fine-tune the rest of its layers on the target domain.

Adversarial Robustness Transfer Learning

Multi-level Knowledge Distillation via Knowledge Alignment and Correlation

1 code implementation1 Dec 2020 Fei Ding, Yin Yang, Hongxin Hu, Venkat Krovi, Feng Luo

While it is important to transfer the full knowledge from teacher to student, we introduce the Multi-level Knowledge Distillation (MLKD) by effectively considering both knowledge alignment and correlation.

Contrastive Learning Knowledge Distillation +2

Interpreting Deep Learning-Based Networking Systems

2 code implementations9 Oct 2019 Zili Meng, Minhu Wang, Jiasong Bai, Mingwei Xu, Hongzi Mao, Hongxin Hu

While many deep learning (DL)-based networking systems have demonstrated superior performance, the underlying Deep Neural Networks (DNNs) remain blackboxes and stay uninterpretable for network operators.

SvTPM: A Secure and Efficient vTPM in the Cloud

1 code implementation21 May 2019 Juan Wang, Chengyang Fan, Jie Wang, Yueqiang Cheng, Yinqian Zhang, Wenhui Zhang, Peng Liu, Hongxin Hu

In this paper, we present SvTPM, a secure and efficient software-based vTPM implementation based on hardware-rooted Trusted Execution Environment (TEE), providing a whole life cycle protection of vTPMs in the cloud.

Cryptography and Security

Rallying Adversarial Techniques against Deep Learning for Network Security

no code implementations27 Mar 2019 Joseph Clements, Yuzhe Yang, Ankur Sharma, Hongxin Hu, Yingjie Lao

Recent advances in artificial intelligence and the increasing need for powerful defensive measures in the domain of network security, have led to the adoption of deep learning approaches for use in network intrusion detection systems.

Network Intrusion Detection

Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards

no code implementations27 Sep 2018 Mhafuzul Islam, Mahsrur Chowdhury, Hongda Li, Hongxin Hu

Vision-based navigation of autonomous vehicles primarily depends on the Deep Neural Network (DNN) based systems in which the controller obtains input from sensors/detectors, such as cameras and produces a vehicle control output, such as a steering wheel angle to navigate the vehicle safely in a roadway traffic environment.

Autonomous Driving Object Detection +2

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