Data Mining Techniques for the Analysis and Prediction in Bioenergy Yield. - Mengyu Ge; Han Liu; Yilin Liu; Changgang Zheng (AIAM (IEEE), 2019)

Planter: seeding trees within switches. - Changgang Zheng; Noa Zilberman (SIGCOMM Posters and Demos, 2021)

Reward-Reinforced Reinforcement Learning for Multi-agent Systems. - Changgang Zheng; Shufan Yang; Juan Marcelo Parra Ullauri; Antonio García-Domínguez; Nelly Bencomo (CoRR, 2021)

Modular neural network via exploring category hierarchy. - Wei Han 009; Changgang Zheng; Rui Zhang 070; Jinxia Guo; Qinli Yang; Junming Shao (Inf. Sci., 2021)

Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures. - Changgang Zheng; Chen Zhen; Haiyong Xie 001; Shufan Yang (DSC, 2022)

Linnet: limit order books within switches. - Xinpeng Hong; Changgang Zheng; Stefan Zohren; Noa Zilberman (SIGCOMM Posters and Demos, 2022)

P4Pir: in-network analysis for smart IoT gateways. - Mingyuan Zang; Changgang Zheng; Radostin Stoyanov; Lars Dittmann; Noa Zilberman (SIGCOMM Posters and Demos, 2022)

IIsy: Practical In-Network Classification. - Changgang Zheng; Zhaoqi Xiong; Thanh T. Bui; Siim Kaupmees; Riyad Bensoussane; Antoine Bernabeu; Shay Vargaftik; Yaniv Ben-Itzhak; Noa Zilberman (CoRR, 2022)

Automating In-Network Machine Learning. - Changgang Zheng; Mingyuan Zang; Xinpeng Hong; Riyad Bensoussane; Shay Vargaftik; Yaniv Ben-Itzhak; Noa Zilberman (CoRR, 2022)

Reducing variations in multi-center Alzheimer's disease classification with convolutional adversarial autoencoder. - Bernard Cobbinah Mawuli; Christian Sorg; Qinli Yang; Arvid Ternblom; Changgang Zheng; Wei Han 009; Liwei Che; Junming Shao (Medical Image Anal., 2022)

Event-driven temporal models for explanations - ETeMoX: explaining reinforcement learning. - Juan Marcelo Parra Ullauri; Antonio García-Domínguez; Nelly Bencomo; Changgang Zheng; Chen Zhen; Juan Boubeta-Puig; Guadalupe Ortiz 001; Shufan Yang (Softw. Syst. Model., 2022)

Reward-Reinforced Generative Adversarial Networks for Multi-Agent Systems. - Changgang Zheng; Shufan Yang; Juan Marcelo Parra Ullauri; Antonio García-Domínguez; Nelly Bencomo (IEEE Trans. Emerg. Top. Comput. Intell., 2022)

LOBIN: In-Network Machine Learning for Limit Order Books. - Xinpeng Hong; Changgang Zheng; Stefan Zohren; Noa Zilberman (HPSR, 2023)

Federated Learning-Based In-Network Traffic Analysis on IoT Edge. - Mingyuan Zang; Changgang Zheng; Tomasz Koziak; Noa Zilberman; Lars Dittmann (IFIP Networking, 2023)

A Novel State Space Exploration Method for the Sparse-Reward Reinforcement Learning Environment. - Xi Liu; Long Ma; Zhen Chen; Changgang Zheng; Ren Chen; Yong Liao; Shufan Yang (SGAI Conf., 2023)

QCMP: Load Balancing via In-Network Reinforcement Learning. - Changgang Zheng; Benjamin Rienecker; Noa Zilberman (FIRA@SIGCOMM, 2023)

A Framework for History-Aware Hyperparameter Optimisation in Reinforcement Learning. - Juan Marcelo Parra Ullauri; Chen Zhen; Antonio García-Domínguez; Nelly Bencomo; Changgang Zheng; Juan Boubeta-Puig; Guadalupe Ortiz 001; Shufan Yang (CoRR, 2023)

DINC: Toward Distributed In-Network Computing. - Changgang Zheng; Haoyue Tang; Mingyuan Zang; Xinpeng Hong; Aosong Feng; Leandros Tassiulas; Noa Zilberman (PACMNET, 2023)

In-Network Machine Learning for Real-Time Transaction Fraud Detection. - Xinpeng Hong; Changgang Zheng; Noa Zilberman (ECAI, 2024)

Accelerating Machine Learning for Trading Using Programmable Switches. - Xinpeng Hong; Changgang Zheng; Stefan Zohren; Noa Zilberman (ECAI, 2024)

E-Commerce Bot Traffic: In-Network Impact, Detection, and Mitigation. - Masoud Hemmatpour; Changgang Zheng; Noa Zilberman (ICIN, 2024)

Reinforcement Learning for Patient Scheduling with Combinatorial Optimisation. - Xi Liu; Changgang Zheng; Zhen Chen; Yong Liao; Ren Chen; Shufan Yang (SGAI Conf. (2), 2024)

GridWatch: A Smart Network for Smart Grid. - Masoud Hemmatpour; Changgang Zheng; Noa Zilberman; Phuong Hoai Ha (SmartGridComm, 2024)

In-Network Machine Learning Using Programmable Network Devices: A Survey. - Changgang Zheng; Xinpeng Hong; Damu Ding; Shay Vargaftik; Yaniv Ben-Itzhak; Noa Zilberman (IEEE Commun. Surv. Tutorials, 2024)

Federated In-Network Machine Learning for Privacy-Preserving IoT Traffic Analysis. - Mingyuan Zang; Changgang Zheng; Tomasz Koziak; Noa Zilberman; Lars Dittmann (ACM Trans. Internet Techn., 2024)

Planter: Rapid Prototyping of In-Network Machine Learning Inference. - Changgang Zheng; Mingyuan Zang; Xinpeng Hong; Liam Perreault; Riyad Bensoussane; Shay Vargaftik; Yaniv Ben-Itzhak; Noa Zilberman (Comput. Commun. Rev., 2024)

Toward Continuous Threat Defense: in-Network Traffic Analysis for IoT Gateways. - Mingyuan Zang; Changgang Zheng; Lars Dittmann; Noa Zilberman (IEEE Internet Things J., 2024)

IIsy: Hybrid In-Network Classification Using Programmable Switches. - Changgang Zheng; Zhaoqi Xiong; Thanh T. Bui; Siim Kaupmees; Riyad Bensoussane; Antoine Bernabeu; Shay Vargaftik; Yaniv Ben-Itzhak; Noa Zilberman (IEEE/ACM Trans. Netw., 2024)

Edge Acceleration of LiDAR Frame Transmission with In-network Machine Learning. - Peng Qian; Changgang Zheng; Noa Zilberman (EdgeSys@EuroSys, 2025)

MUTA: Enabling Multi-Task Neural Network Inference in Programmable Data-Planes. - Kaiyi Zhang 005; Changgang Zheng; Nancy Samaan; Ahmed Karmouch; Noa Zilberman (HPSR, 2025)