b'Yi Shi'

Polyphone Disambiguition in Mandarin Chinese with Semi-Supervised Learning

The majority of Chinese characters are monophonic, i.e.their pronunciati...
02/01/2021 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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

Network slicing manages network resources as virtual resource blocks (RB...
01/21/2021 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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

Reinforcement learning (RL) for network slicing is considered in the 5G ...
01/14/2021 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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Adversarial Machine Learning for 5G Communications Security

Machine learning provides automated means to capture complex dynamics of...
01/07/2021 ∙ by Yalin E. Sagduyu, et al. ∙ 41 ∙ share

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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...
11/28/2020 ∙ by Tao Xiong, et al. ∙ 0 ∙ share

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

The paper presents a reinforcement learning solution to dynamic resource...
09/14/2020 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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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...
08/27/2020 ∙ by Sudeep Fadadu, et al. ∙ 4 ∙ share

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

The spoofing attack is critical to bypass physical-layer signal authenti...
07/16/2020 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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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...
06/25/2020 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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Deep Learning for Wireless Communications

Existing communication systems exhibit inherent limitations in translati...
05/12/2020 ∙ by Tugba Erpek, et al. ∙ 0 ∙ share

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

Wireless systems are vulnerable to various attacks such as jamming and e...
01/24/2020 ∙ by Yalin E. Sagduyu, et al. ∙ 0 ∙ share

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Coherent Communications in Self-Organizing Networks with Distributed Beamforming

Coherent communications aim to support higher data rates and extended co...
12/20/2019 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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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 ...
12/11/2019 ∙ by Sohraab Soltani, et al. ∙ 0 ∙ share

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

An adversarial deep learning approach is presented to launch over-the-ai...
11/01/2019 ∙ by Yalin E. Sagduyu, et al. ∙ 0 ∙ share

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QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning

The problem of quality of service (QoS) and jamming-aware communications...
10/13/2019 ∙ by Nof Abuzainab, et al. ∙ 0 ∙ share

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

Dynamic spectrum access (DSA) benefits from detection and classification...
09/25/2019 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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IoT Network Security from the Perspective of Adversarial Deep Learning

Machine learning finds rich applications in Internet of Things (IoT) net...
05/31/2019 ∙ by Yalin E. Sagduyu, et al. ∙ 0 ∙ share

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Generative Adversarial Network for Wireless Signal Spoofing

The paper presents a novel approach of spoofing wireless signals by usin...
05/03/2019 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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Spectrum Data Poisoning with Adversarial Deep Learning

Machine learning has been widely applied in wireless communications. How...
01/26/2019 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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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...
01/25/2019 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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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...
11/05/2018 ∙ by Yi Shi, et al. ∙ 0 ∙ share

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Deep Learning for Launching and Mitigating Wireless Jamming Attacks

An adversarial machine learning approach is introduced to launch jamming...
07/03/2018 ∙ by Tugba Erpek, et al. ∙ 0 ∙ share

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Deep Supervised Hashing with Triplet Labels

Hashing is one of the most popular and powerful approximate nearest neig...
12/12/2016 ∙ by Xiaofang Wang, et al. ∙ 0 ∙ share

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Yi Shi

Featured Co-authors

Yu Chen

Bin Wang

Yalin E. Sagduyu

Kris M. Kitani

Volkan Isler

M. Cenk Gursoy

Tugba Erpek

Nemanja Djuric

Xiaofang Wang

Kemal Davaslioglu

Aylin Yener

Polyphone Disambiguition in Mandarin Chinese with Semi-Supervised Learning

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

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

Adversarial Machine Learning for 5G Communications Security

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

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

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

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

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

Deep Learning for Wireless Communications

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

Coherent Communications in Self-Organizing Networks with Distributed Beamforming

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

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

QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning

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

IoT Network Security from the Perspective of Adversarial Deep Learning

Generative Adversarial Network for Wireless Signal Spoofing

Spectrum Data Poisoning with Adversarial Deep Learning

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

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

Deep Learning for Launching and Mitigating Wireless Jamming Attacks

Deep Supervised Hashing with Triplet Labels