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Yi Shi

14 papers hereh-index 16952 citations27 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author10
  • middle author3
  • last author1

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.NI7
  • cs.LG3
  • eess.SP3
  • cs.CR1
same name
  • Yi Shi — 25 papers, h 19
  • Yi Shi — 22 papers, h 8
  • Yi Shi — 15 papers, h 53
  • Yi Shi — 11 papers, h 45
  • Yi Shi — 9 papers, h 13
  • Yi Shi — 8 papers, h 52

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182023
most citedGenerative Adversarial Network for Wireless Signal Spoofing

10 citations · 28 across the 13 of their papers we have counts for

collaborators
Showing 2019 · cs.NIShow all

4 papers · 2 filters

cs.NI2019

QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning

Nof Abuzainab, Tugba Erpek, Kemal Davaslioglu +8

The problem of quality of service (QoS) and jamming-aware communications is considered in an adversarial wireless network subject to external eavesdropping and jamming attacks. To…

cs.NI2019★ 4 cited

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

Yi Shi, Kemal Davaslioglu, Yalin E. Sagduyu +3

Dynamic spectrum access (DSA) benefits from detection and classification of interference sources including in-network users, out-network users, and jammers that may all coexist in…

cs.NI2019

IoT Network Security from the Perspective of Adversarial Deep Learning

Yalin E. Sagduyu, Yi Shi, Tugba Erpek

Machine learning finds rich applications in Internet of Things (IoT) networks such as information retrieval, traffic management, spectrum sensing, and signal authentication. While…

cs.NI2019★ 2 cited

Spectrum Data Poisoning with Adversarial Deep Learning

Yi Shi, Tugba Erpek, Yalin E. Sagduyu +1

Machine learning has been widely applied in wireless communications. However, the security aspects of machine learning in wireless applications have not been well understood yet. W…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.