| 2024 | EMNLP | Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models. | Yae Jee Cho, Luyang Liu, Zheng Xu, Aldi Fahrezi, Gauri Joshi |
| 2023 | ICCV | Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels. | Yae Jee Cho, Gauri Joshi, Dimitrios Dimitriadis |
| 2023 | ICML | On the Convergence of Federated Averaging with Cyclic Client Participation. | Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang |
| 2022 | AISTATS | Towards Understanding Biased Client Selection in Federated Learning. | Yae Jee Cho, Jianyu Wang, Gauri Joshi |
| 2022 | IJCAI | Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning. | Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis |
| 2020 | ACSSC | Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning. | Yae Jee Cho, Samarth Gupta, Gauri Joshi, Osman Yagan |
| 2018 | GLOBECOM | V2X Downlink Coverage Analysis with a Realistic Urban Vehicular Model. | Yae Jee Cho, Kaibin Huang, Chan-Byoung Chae |
| 2017 | WCNC | Effective Enzyme Deployment for Degradation of Interference Molecules in Molecular Communication. | Yae Jee Cho, H. Birkan Yilmaz, Weisi Guo, Chan-Byoung Chae |