b'Yi Shi'

research

∙ 06/01/2023

Controllable Motion Diffusion Model

Generating realistic and controllable motions for virtual characters is ...

17 Yi Shi, et al. ∙

research

∙ 01/14/2023

Design of GNSS-RTK Landslide Monitoring System Based on Improved Raida Criterion

Aiming at the problem that GNSS-RTK technology cannot effectively monito...

0 Junming Wang, et al. ∙

research

∙ 01/12/2023

Jamming Attacks on Decentralized Federated Learning in General Multi-Hop Wireless Networks

Decentralized federated learning (DFL) is an effective approach to train...

0 Yi Shi, et al. ∙

research

∙ 12/27/2022

Sensing-Throughput Tradeoffs with Generative Adversarial Networks for NextG Spectrum Sharing

Spectrum coexistence is essential for next generation (NextG) systems to...

0 Yi Shi, et al. ∙

research

∙ 11/30/2022

A fully asymptotic preserving decomposed multi-group method for the frequency-dependent radiative transfer equations

The opacity of FRTE depends on not only the material temperature but als...

0 Xiaojiang Zhang, et al. ∙

research

∙ 10/08/2022

Rethinking the Detection Head Configuration for Traffic Object Detection

Multi-scale detection plays an important role in object detection models...

0 Yi Shi, et al. ∙

research

∙ 04/08/2022

Identifying Ambiguous Similarity Conditions via Semantic Matching

Rich semantics inside an image result in its ambiguous relationship with...

0 Han-Jia Ye, et al. ∙

research

∙ 04/06/2022

Federated Learning for Distributed Spectrum Sensing in NextG Communication Networks

NextG networks are intended to provide the flexibility of sharing the sp...

0 Yi Shi, et al. ∙

research

∙ 01/13/2022

Jamming Attacks on Federated Learning in Wireless Networks

Federated learning (FL) offers a decentralized learning environment so t...

0 Yi Shi, et al. ∙

research

∙ 10/26/2021

C^2SP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction

Recent development in brain-machine interface technology has made seizur...

13 Di Wu, et al. ∙

research

∙ 10/15/2021

A novel framework to quantify uncertainty in peptide-tandem mass spectrum matches with application to nanobody peptide identification

Nanobodies are small antibody fragments derived from camelids that selec...

0 Chris McKennan, et al. ∙

research

∙ 09/16/2021

Adversarial Attacks against Deep Learning Based Power Control in Wireless Communications

We consider adversarial machine learning based attacks on power allocati...

0 Brian Kim, et al. ∙

research

∙ 07/22/2021

Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learning

An over-the-air membership inference attack (MIA) is presented to leak p...

0 Yi Shi, et al. ∙

research

∙ 03/26/2021

Improve GAN-based Neural Vocoder using Pointwise Relativistic LeastSquare GAN

GAN-based neural vocoders, such as Parallel WaveGAN and MelGAN have attr...

0 Congyi Wang, et al. ∙

research

∙ 02/01/2021

Polyphone Disambiguition in Mandarin Chinese with Semi-Supervised Learning

The majority of Chinese characters are monophonic, i.e.their pronunciati...

0 Yi Shi, et al. ∙

research

∙ 01/21/2021

Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing

Network slicing manages network resources as virtual resource blocks (RB...

0 Yi Shi, et al. ∙

research

∙ 01/14/2021

How to Attack and Defend 5G Radio Access Network Slicing with Reinforcement Learning

Reinforcement learning (RL) for network slicing is considered in the 5G ...

0 Yi Shi, et al. ∙

research

∙ 01/07/2021

Adversarial Machine Learning for 5G Communications Security

Machine learning provides automated means to capture complex dynamics of...

41 Yalin E. Sagduyu, et al. ∙

research

∙ 11/28/2020

High order asymptotic preserving discontinuous Galerkin methods for gray radiative transfer equations

In this paper, we will develop a class of high order asymptotic preservi...

0 Tao Xiong, et al. ∙

research

∙ 09/14/2020

Reinforcement Learning for Dynamic Resource Optimization in 5G Radio Access Network Slicing

The paper presents a reinforcement learning solution to dynamic resource...

0 Yi Shi, et al. ∙

research

∙ 08/27/2020

Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving

We present an end-to-end method for object detection and trajectory pred...

4 Sudeep Fadadu, et al. ∙

research

∙ 07/16/2020

Generative Adversarial Network in the Air: Deep Adversarial Learning for Wireless Signal Spoofing

The spoofing attack is critical to bypass physical-layer signal authenti...

0 Yi Shi, et al. ∙

research

∙ 06/25/2020

Over-the-Air Membership Inference Attacks as Privacy Threats for Deep Learning-based Wireless Signal Classifiers

This paper presents how to leak private information from a wireless sign...

0 Yi Shi, et al. ∙

research

∙ 05/12/2020

Deep Learning for Wireless Communications

Existing communication systems exhibit inherent limitations in translati...

0 Tugba Erpek, et al. ∙

research

∙ 01/24/2020

When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions

Wireless systems are vulnerable to various attacks such as jamming and e...

0 Yalin E. Sagduyu, et al. ∙

research

∙ 12/20/2019

Coherent Communications in Self-Organizing Networks with Distributed Beamforming

Coherent communications aim to support higher data rates and extended co...

0 Yi Shi, et al. ∙

research

∙ 12/11/2019

Cross-layer Design and SDR Implementation of DSA, Backpressure Routing and Network Coding

A cross-layer cognitive radio system is designed to support unicast and ...

0 Sohraab Soltani, et al. ∙

research

∙ 11/01/2019

Adversarial Deep Learning for Over-the-Air Spectrum Poisoning Attacks

An adversarial deep learning approach is presented to launch over-the-ai...

0 Yalin E. Sagduyu, et al. ∙

research

∙ 10/13/2019

QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning

The problem of quality of service (QoS) and jamming-aware communications...

0 Nof Abuzainab, et al. ∙

research

∙ 09/25/2019

Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments

Dynamic spectrum access (DSA) benefits from detection and classification...

0 Yi Shi, et al. ∙

research

∙ 05/31/2019

IoT Network Security from the Perspective of Adversarial Deep Learning

Machine learning finds rich applications in Internet of Things (IoT) net...

0 Yalin E. Sagduyu, et al. ∙

research

∙ 05/03/2019

Generative Adversarial Network for Wireless Signal Spoofing

The paper presents a novel approach of spoofing wireless signals by usin...

0 Yi Shi, et al. ∙

research

∙ 01/26/2019

Spectrum Data Poisoning with Adversarial Deep Learning

Machine learning has been widely applied in wireless communications. How...

0 Yi Shi, et al. ∙

research

∙ 01/25/2019

Generative Adversarial Networks for Black-Box API Attacks with Limited Training Data

As online systems based on machine learning are offered to public or pai...

0 Yi Shi, et al. ∙

research

∙ 11/05/2018

Active Deep Learning Attacks under Strict Rate Limitations for Online API Calls

Machine learning has been applied to a broad range of applications and s...

0 Yi Shi, et al. ∙

research

∙ 07/03/2018

Deep Learning for Launching and Mitigating Wireless Jamming Attacks

An adversarial machine learning approach is introduced to launch jamming...

0 Tugba Erpek, et al. ∙

research

∙ 12/12/2016

Deep Supervised Hashing with Triplet Labels

Hashing is one of the most popular and powerful approximate nearest neig...

0 Xiaofang Wang, et al. ∙

Yi Shi

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