Changgang Zheng

Orcid: 0000-0003-1894-722X

According to our database1, Changgang Zheng authored at least 27 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
IIsy: Hybrid In-Network Classification Using Programmable Switches.
IEEE/ACM Trans. Netw., June, 2024

Toward Continuous Threat Defense: in-Network Traffic Analysis for IoT Gateways.
IEEE Internet Things J., March, 2024

Planter: Rapid Prototyping of In-Network Machine Learning Inference.
Comput. Commun. Rev., January, 2024

In-Network Machine Learning Using Programmable Network Devices: A Survey.
IEEE Commun. Surv. Tutorials, 2024

GridWatch: A Smart Network for Smart Grid.
Proceedings of the IEEE International Conference on Communications, 2024

Reinforcement Learning for Patient Scheduling with Combinatorial Optimisation.
Proceedings of the Artificial Intelligence XLI, 2024

E-Commerce Bot Traffic: In-Network Impact, Detection, and Mitigation.
Proceedings of the 27th Conference on Innovation in Clouds, Internet and Networks, 2024

Accelerating Machine Learning for Trading Using Programmable Switches.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

In-Network Machine Learning for Real-Time Transaction Fraud Detection.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023
DINC: Toward Distributed In-Network Computing.
PACMNET, 2023

A Framework for History-Aware Hyperparameter Optimisation in Reinforcement Learning.
CoRR, 2023

QCMP: Load Balancing via In-Network Reinforcement Learning.
Proceedings of the 2nd ACM SIGCOMM Workshop on Future of Internet Routing & Addressing, 2023

A Novel State Space Exploration Method for the Sparse-Reward Reinforcement Learning Environment.
Proceedings of the Artificial Intelligence XL, 2023

Federated Learning-Based In-Network Traffic Analysis on IoT Edge.
Proceedings of the IFIP Networking Conference, 2023

LOBIN: In-Network Machine Learning for Limit Order Books.
Proceedings of the 24th IEEE International Conference on High Performance Switching and Routing, 2023

2022
Reward-Reinforced Generative Adversarial Networks for Multi-Agent Systems.
IEEE Trans. Emerg. Top. Comput. Intell., 2022

Event-driven temporal models for explanations - ETeMoX: explaining reinforcement learning.
Softw. Syst. Model., 2022

Reducing variations in multi-center Alzheimer's disease classification with convolutional adversarial autoencoder.
Medical Image Anal., 2022

Automating In-Network Machine Learning.
CoRR, 2022

IIsy: Practical In-Network Classification.
CoRR, 2022

P4Pir: in-network analysis for smart IoT gateways.
Proceedings of the SIGCOMM '22 Poster and Demo Sessions, 2022

Linnet: limit order books within switches.
Proceedings of the SIGCOMM '22 Poster and Demo Sessions, 2022

Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures.
Proceedings of the IEEE Conference on Dependable and Secure Computing, 2022

2021
Modular neural network via exploring category hierarchy.
Inf. Sci., 2021

Reward-Reinforced Reinforcement Learning for Multi-agent Systems.
CoRR, 2021

Planter: seeding trees within switches.
Proceedings of the SIGCOMM '21: ACM SIGCOMM 2021 Conference, 2021

2019
Data Mining Techniques for the Analysis and Prediction in Bioenergy Yield.
Proceedings of the International Conference on Artificial Intelligence and Advanced Manufacturing, 2019


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