| Theory on forgetting and generalization of continual learning S Lin, P Ju, Y Liang, N Shroff International Conference on Machine Learning, 21078-21100, 2023 | 47 | 2023 |
| Generalized spatial modulation with transmit antenna grouping for massive MIMO P Ju, M Zhang, X Cheng, L Yang 2017 IEEE International Conference on Communications (ICC), 2017 | 38 | 2017 |
| Overfitting can be harmless for basis pursuit, but only to a degree P Ju, X Lin, J Liu Advances in Neural Information Processing Systems 33, 7956-7967, 2020 | 24 | 2020 |
| Adversarial attacks to distributed voltage control in power distribution networks with DERs P Ju, X Lin Proceedings of the Ninth International Conference on Future Energy Systems …, 2018 | 23 | 2018 |
| Generalized spatial modulation with transmit antenna grouping for correlated channels P Ju, M Zhang, X Cheng, CX Wang, L Yang 2016 IEEE International Conference on Communications (ICC), 1-6, 2016 | 22 | 2016 |
| On the generalization power of overfitted two-layer neural tangent kernel models P Ju, X Lin, N Shroff International Conference on Machine Learning, 5137-5147, 2021 | 13 | 2021 |
| Achievable-rate-enhancing self-interference cancellation for full-duplex communications P Ju, M Wen, X Cheng, L Yang IEEE Transactions on Wireless Communications 17 (12), 8473-8484, 2018 | 13 | 2018 |
| Non-asymptotic convergence of discrete-time diffusion models: New approach and improved rate Y Liang, P Ju, Y Liang, N Shroff arXiv e-prints, arXiv: 2402.13901, 2024 | 10 | 2024 |
| On the generalization power of the overfitted three-layer neural tangent kernel model P Ju, X Lin, N Shroff Advances in neural information processing systems 35, 26135-26146, 2022 | 10 | 2022 |
| An effective self-interference cancellation scheme for spatial modulated full duplex systems P Ju, M Wen, X Cheng, L Yang 2015 IEEE International Conference on Communications (ICC), 2123-2128, 2015 | 7 | 2015 |
| Achieving fairness in multi-agent MDP using reinforcement learning P Ju, A Ghosh, N Shroff The Twelfth International Conference on Learning Representations, 2023 | 6 | 2023 |
| Theoretical characterization of the generalization performance of overfitted meta-learning P Ju, Y Liang, NB Shroff arXiv preprint arXiv:2304.04312, 2023 | 5 | 2023 |
| Broadening target distributions for accelerated diffusion models via a novel analysis approach Y Liang, P Ju, Y Liang, N Shroff arXiv preprint arXiv:2402.13901, 2024 | 4 | 2024 |
| Generalization performance of transfer learning: Overparameterized and underparameterized regimes P Ju, S Lin, MS Squillante, Y Liang, NB Shroff arXiv preprint arXiv:2306.04901, 2023 | 4 | 2023 |
| Achieving fairness in multi-agent markov decision processes using reinforcement learning P Ju, A Ghosh, NB Shroff arXiv preprint arXiv:2306.00324, 2023 | 3 | 2023 |
| Distribution-level markets under high renewable energy penetration P Ju, X Lin, J Huang Proceedings of the Thirteenth ACM International Conference on Future Energy …, 2022 | 3 | 2022 |
| PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization M Xu, P Ju, J Liu, H Yang arXiv preprint arXiv:2412.10961, 2024 | 2 | 2024 |
| Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning? P Ju, H Yang, J Liu, Y Liang, N Shroff Proceedings of the Twenty-fifth International Symposium on Theory …, 2024 | 1 | 2024 |
| AI‐EDGE: An NSF AI institute for future edge networks and distributed intelligence P Ju, C Li, Y Liang, N Shroff AI Magazine 45 (1), 29-34, 2024 | 1 | 2024 |
| Understanding the Generalization Power of Overfitted NTK Models: 3-layer vs. 2-layer P Ju, X Lin, NB Shroff 2022 58th Annual Allerton Conference on Communication, Control, and …, 2022 | 1 | 2022 |
Ness ShroffDepartment of ECE and CSE, The Ohio State UniversityVerified email at osu.edu