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ORCIDDong-Young Lim
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2020 – today
- 2025
[j3]Dong-Young Lim
, Ariel Neufeld, Sotirios Sabanis, Ying Zhang:
Langevin Dynamics Based Algorithm e-THεO POULA for Stochastic Optimization Problems with Discontinuous Stochastic Gradient. Math. Oper. Res. 50(3): 2333-2374 (2025)- [j2]Stefano Bruno, Ying Zhang, Dongyoung Lim, Ömer Deniz Akyildiz, Sotirios Sabanis:
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates. Trans. Mach. Learn. Res. 2025 (2025) - [c7]YongKyung Oh, Dong-Young Lim, Sungil Kim:
DualDynamics: Synergizing Implicit and Explicit Methods for Robust Irregular Time Series Analysis. AAAI 2025: 19730-19739 - [c6]Yongkyung Oh, Dongyoung Lim, Sungil Kim, Alex A. T. Bui:
TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification. CIKM 2025: 2232-2242 - [c5]Yongkyung Oh, Seungsu Kam, Dongyoung Lim, Sungil Kim:
Modeling Irregular Astronomical Time Series with Neural Stochastic Delay Differential Equations. CIKM 2025: 5068-5073 - [c4]Yongkyung Oh, Dongyoung Lim, Sungil Kim:
Neural Differential Equations for Continuous-Time Analysis. CIKM 2025: 6837-6840 - [c3]YongKyung Oh, Seungsu Kam, Jonghun Lee, Dong-Young Lim, Sungil Kim, Alex A. T. Bui:
Comprehensive Review of Neural Differential Equations for Time Series Analysis. IJCAI 2025: 10621-10631 - [i15]YongKyung Oh, Seungsu Kam, Jonghun Lee, Dong-Young Lim, Sungil Kim, Alex A. T. Bui:
Comprehensive Review of Neural Differential Equations for Time Series Analysis. CoRR abs/2502.09885 (2025) - [i14]Youngjun Song, Youngsik Hwang, Jonghun Lee, Heechang Lee, Dong-Young Lim:
DGSAM: Domain Generalization via Individual Sharpness-Aware Minimization. CoRR abs/2503.23430 (2025) - [i13]YongKyung Oh, Dong-Young Lim, Sungil Kim, Alex A. T. Bui:
TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification. CoRR abs/2508.17519 (2025) - [i12]YongKyung Oh, Seungsu Kam, Dong-Young Lim, Sungil Kim:
Modeling Irregular Astronomical Time Series with Neural Stochastic Delay Differential Equations. CoRR abs/2508.17521 (2025) - [i11]Stefano Bruno, Youngsik Hwang, Jaehyeon An, Sotirios Sabanis, Dong-Young Lim:
Flatness-Aware Stochastic Gradient Langevin Dynamics. CoRR abs/2510.02174 (2025) - [i10]Youngsik Hwang, Dong-Young Lim:
Controllable Machine Unlearning via Gradient Pivoting. CoRR abs/2510.19226 (2025) - [i9]Jonghun Lee, YongKyung Oh, Sungil Kim, Dong-Young Lim:
Continuum Dropout for Neural Differential Equations. CoRR abs/2511.10446 (2025) - [i8]YongKyung Oh, Dong-Young Lim, Sungil Kim:
FlowPath: Learning Data-Driven Manifolds with Invertible Flows for Robust Irregularly-sampled Time Series Classification. CoRR abs/2511.10841 (2025) - 2024
- [j1]Dong-Young Lim, Sotirios Sabanis:
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks. J. Mach. Learn. Res. 25: 53:1-53:52 (2024) - [c2]YongKyung Oh, Dongyoung Lim, Sungil Kim:
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data. ICLR 2024 - [c1]Youngsik Hwang, Dong-Young Lim:
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks. NeurIPS 2024 - [i7]YongKyung Oh, Dongyoung Lim, Sungil Kim:
Invertible Solution of Neural Differential Equations for Analysis of Irregularly-Sampled Time Series. CoRR abs/2401.04979 (2024) - [i6]YongKyung Oh, Dongyoung Lim, Sungil Kim:
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data. CoRR abs/2402.14989 (2024) - [i5]Youngsik Hwang, Dong-Young Lim:
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks. CoRR abs/2409.18426 (2024) - 2023
- [i4]Stefano Bruno, Ying Zhang, Dong-Young Lim, Ömer Deniz Akyildiz, Sotirios Sabanis:
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates. CoRR abs/2311.13584 (2023) - 2022
- [i3]Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang:
Langevin dynamics based algorithm e-THεO POULA for stochastic optimization problems with discontinuous stochastic gradient. CoRR abs/2210.13193 (2022) - 2021
- [i2]Dong-Young Lim, Sotirios Sabanis:
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks. CoRR abs/2105.13937 (2021) - [i1]Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang:
Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function. CoRR abs/2107.08649 (2021)
Coauthor Index
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