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Youngdae Kim
Person information
- affiliation: KAIST
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2020 – today
- 2024
- [c9]Sihan Zeng, Youngdae Kim, Yuxuan Ren, Kibaek Kim:
QCQP-Net: Reliably learning feasible alternating current optimal power flow solutions under constraints. L4DC 2024: 1539-1551 - [i6]Sihan Zeng, Youngdae Kim, Yuxuan Ren, Kibaek Kim:
QCQP-Net: Reliably Learning Feasible Alternating Current Optimal Power Flow Solutions Under Constraints. CoRR abs/2401.06820 (2024) - 2023
- [c8]Daehyun Chang, Youngdae Kim, Suksoo Pyo, Shin Hun, Daesop Lee, Sohee Hwang, Jaesik Choi, Siwoong Kim:
Algorithmic Read Resistance Trim for Improving Yield and Reducing Test Time in MRAM. ITC 2023: 87-92 - 2022
- [c7]Youngdae Kim, Kibaek Kim:
Accelerated Computation and Tracking of AC Optimal Power Flow Solutions Using GPUs. ICPP Workshops 2022: 19:1-19:8 - [c6]Vishwas Rao, Anirudh Subramanyam, Michel Schanen, Youngdae Kim, Ignas Satkauskas, Mihai Anitescu
:
Frequency Recovery in Power Grids using High-Performance Computing. ICPP Workshops 2022: 20:1-20:6 - [c5]Minseok Ryu, Youngdae Kim, Kibaek Kim, Ravi K. Madduri
:
APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning. IPDPS Workshops 2022: 1074-1083 - [i5]Minseok Ryu, Youngdae Kim, Kibaek Kim, Ravi K. Madduri:
APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning. CoRR abs/2202.03672 (2022) - [i4]Youngdae Kim, Debojyoti Ghosh, Emil M. Constantinescu
, Ramesh Balakrishnan:
GPU-Accelerated WENO Schemes for DNS of Compressible Turbulent Flows. CoRR abs/2211.16718 (2022) - 2021
- [j7]Noam Goldberg, Steffen Rebennack
, Youngdae Kim, Vitaliy Krasko, Sven Leyffer
:
MINLP formulations for continuous piecewise linear function fitting. Comput. Optim. Appl. 79(1): 223-233 (2021) - [i3]Youngdae Kim, François Pacaud, Kibaek Kim, Mihai Anitescu:
Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition. CoRR abs/2106.14995 (2021) - [i2]Sihan Zeng, Alyssa Kody, Youngdae Kim, Kibaek Kim, Daniel K. Molzahn:
A Reinforcement Learning Approach to Parameter Selection for Distributed Optimization in Power Systems. CoRR abs/2110.11991 (2021)
2010 – 2019
- 2019
- [j6]Youngdae Kim, Michael C. Ferris
:
Solving equilibrium problems using extended mathematical programming. Math. Program. Comput. 11(3): 457-501 (2019) - 2018
- [j5]Youngdae Kim, Olivier Huber
, Michael C. Ferris
:
A structure-preserving pivotal method for affine variational inequalities. Math. Program. 168(1-2): 93-121 (2018) - [i1]Youngdae Kim, Michael C. Ferris:
Solving equilibrium problems using extended mathematical programming. CoRR abs/1806.02255 (2018) - 2014
- [j4]Noam Goldberg
, Youngdae Kim, Sven Leyffer
, Thomas D. Veselka:
Adaptively refined dynamic program for linear spline regression. Comput. Optim. Appl. 58(3): 523-541 (2014) - [j3]Youngdae Kim, Ilhwan Ko, Wook-Shin Han, Hwanjo Yu:
iKernel: Exact indexing for support vector machines. Inf. Sci. 257: 32-53 (2014) - 2012
- [j2]Hwanjo Yu, Jinha Kim, Youngdae Kim, Seung-won Hwang, Young Ho Lee:
An efficient method for learning nonlinear ranking SVM functions. Inf. Sci. 209: 37-48 (2012) - 2011
- [c4]Hwanjo Yu, Ilhwan Ko, Youngdae Kim, Seung-won Hwang, Wook-Shin Han:
Exact indexing for support vector machines. SIGMOD Conference 2011: 709-720
2000 – 2009
- 2009
- [j1]Youngdae Kim, Gae-won You, Seung-won Hwang:
Ranking strategies and threats: a cost-based pareto optimization approach. Distributed Parallel Databases 26(1): 127-150 (2009) - [c3]Hwanjo Yu, Youngdae Kim, Seung-won Hwang:
RV-SVM: An Efficient Method for Learning Ranking SVM. PAKDD 2009: 426-438 - 2008
- [c2]Youngdae Kim, Gae-won You, Seung-won Hwang:
Escaping a Dominance Region at Minimum Cost. DEXA 2008: 800-807 - [c1]Youngdae Kim, Seung-won Hwang:
Approximate Boolean + Ranking Query Answering Using Wavelets. WAIM 2008: 17-24
Coauthor Index
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last updated on 2024-08-05 20:17 CEST by the dblp team
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