| Modems: Optimizing edge computing migrations for user mobility T Kim, SD Sathyanarayana, S Chen, Y Im, X Zhang, S Ha, C Joe-Wong IEEE Journal on Selected Areas in Communications 41 (3), 675-689, 2022 | 36 | 2022 |
| Characterizing internal evasion attacks in federated learning T Kim, S Singh, N Madaan, C Joe-Wong International Conference on Artificial Intelligence and Statistics, 907-921, 2023 | 11 | 2023 |
| Can we generalize and distribute private representation learning? SS Azam, T Kim, S Hosseinalipour, C Joe-Wong, S Bagchi, C Brinton International Conference on Artificial Intelligence and Statistics, 11320-11340, 2022 | 10 | 2022 |
| An integrated visible-light and radio frequency communications system P Dhulipalla, M Kang, T Kim, N Tan, S Govindasamy, MB Rahaim 2019 International Conference on Computer, Information and Telecommunication …, 2019 | 8 | 2019 |
| pFedDef: Defending grey-box attacks for personalized federated learning T Kim, S Singh, N Madaan, C Joe-Wong arXiv preprint arXiv:2209.08412, 2022 | 7 | 2022 |
| Towards generalized and distributed privacy-preserving representation learning SS Azam, T Kim, S Hosseinalipour, C Brinton, C Joe-Wong, S Bagchi arXiv preprint arXiv:2010.01792, 2020 | 7 | 2020 |
| pFedDef: Characterizing evasion attack transferability in federated learning T Kim, S Singh, N Madaan, C Joe-Wong Software Impacts 15, 100469, 2023 | 4 | 2023 |
| Toward effective moving target defense against adversarial ai P Martin, J Fan, T Kim, K Vesey, L Greenwald MILCOM 2021-2021 IEEE Military Communications Conference (MILCOM), 993-998, 2021 | 4 | 2021 |
| Edge-MSL: Split Learning on the Mobile Edge via Multi-Armed Bandits T Kim, J Zuo, X Zhang, C Joe-Wong IEEE INFOCOM 2024-IEEE Conference on Computer Communications, 391-400, 2024 | 1 | 2024 |
| Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning T Kim, J Li, S Singh, N Madaan, C Joe-Wong arXiv preprint arXiv:2310.11594, 2023 | | 2023 |
| Optimizing Distributed Machine Learning on User-Variant Edge Computing Systems T Kim Carnegie Mellon University, 2023 | | 2023 |
| Federated Learning Transfers Evasion Attacks T Kim | | 2021 |
| Can we Generalize and Distribute Private Representation Learning? S Shams Azam, T Kim, S Hosseinalipour, C Joe-Wong, S Bagchi, ... arXiv e-prints, arXiv: 2010.01792, 2020 | | 2020 |
| An 802.11 Compatible Asymmetric Hybrid Visible-Light and Radio-Frequency Communications System M Goldwater, P Dhulipalla, M Kang, T Kim, N Tan, S Govindasamy, ... 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile …, 2020 | | 2020 |
| A Generalized and Distributable Generative Model for Private Representation Learning SS Azam, T Kim, S Hosseinalipour, C Joe-Wong, S Bagchi, C Brinton NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications, 0 | | |
| POSTER: GREY-BOX DEFENSE FOR PERSONALIZED FEDERATED LEARNING T Kim, N Madaan, S Singh, C Joe-Wong | | |
| Technical Report: Approaches for shared use of base-band hardware in OFDM-based hybrid VLC-RF Systems with multicolored LEDs P Dhulipala, M Kang, T Kim, S Govindasamy | | |
