| Trimming the Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning J Yun, P Zheng, E Yang, A Lozano, A Aravkin International Conference on Machine Learning, 7242-7251, 2019 | 31 | 2019 |
| Adaptive proximal gradient methods for structured neural networks J Yun, AC Lozano, E Yang Advances in Neural Information Processing Systems 34, 24365-24378, 2021 | 25 | 2021 |
| A general family of stochastic proximal gradient methods for deep learning J Yun, AC Lozano, E Yang arXiv preprint arXiv:2007.07484, 2020 | 15 | 2020 |
| Cluster-promoting quantization with bit-drop for minimizing network quantization loss JH Lee, J Yun, SJ Hwang, E Yang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 14 | 2021 |
| Lantern: Accelerating visual autoregressive models with relaxed speculative decoding D Jang, S Park, JY Yang, Y Jung, J Yun, S Kundu, SY Kim, E Yang arXiv preprint arXiv:2410.03355, 2024 | 7 | 2024 |
| Riemannian SAM: sharpness-aware minimization on riemannian manifolds J Yun, E Yang Advances in Neural Information Processing Systems 36, 65784-65800, 2023 | 6 | 2023 |
| Adablock: SGD with practical block diagonal matrix adaptation for deep learning J Yun, A Lozano, E Yang International Conference on Artificial Intelligence and Statistics, 2574-2606, 2022 | 4 | 2022 |
| Stochastic gradient methods with block diagonal matrix adaptation J Yun, AC Lozano, E Yang arXiv preprint arXiv:1905.10757, 2019 | 4 | 2019 |
| M-estimation with the trimmed l1 penalty J Yun, P Zheng, E Yang, A Lozano, A Aravkin arXiv preprint arXiv:1805.07495, 2018 | 3 | 2018 |
| TEDDY: Trimming edges with degree-based discrimination strategy H Seo, J Yun, E Yang arXiv preprint arXiv:2402.01261, 2024 | 1 | 2024 |
| Trimming the l-1 Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning J Yun, P Zheng, E Yang, A Lozano, A Aleksandr Thirty-sixth International Conference on Machine Learning, 2019 | 1 | 2019 |
| Unraveling Zeroth-Order Optimization through the Lens of Low-Dimensional Structured Perturbations S Park, J Yun, SY Kim, S Kundu, E Yang arXiv preprint arXiv:2501.19099, 2025 | | 2025 |
| Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bitwise Regularization JH Lee, J Yun, SJ Hwang, E Yang | | 2019 |
| MeZO-Adam: Memory-efficient Zeroth-order Adam with Adaptivity Adjustments for Fine-tuning LLMs S Park, J Yun, SY Kim, JY Yang, Y Jung, S Kundu, K Kim, E Yang | | |
| Revised NTK Analysis of Optimization and Generalization with Its Extensions to Arbitrary Initialization J Yun, K Kim, E Yang | | |
| GradientMix: A Simple yet Effective Regularization for Large Batch Training J Yun, JH Lee, E Yang | | |
Eunho YangKAISTPreverjeni e-poštni naslov na kaist.ac.kr