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Kibaek Kim
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2020 – today
- 2024
- [j9]Geunyeong Byeon, Kibaek Kim:
Distributionally Robust Decentralized Volt-Var Control With Network Reconfiguration. IEEE Trans. Smart Grid 15(5): 4705-4718 (2024) - [c10]Grant Wilkins, Sheng Di, Jon C. Calhoun, Zilinghan Li, Kibaek Kim, Robert Underwood, Richard Mortier, Franck Cappello:
FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications. ICDCS 2024: 577-588 - [c9]Zilinghan Li, Pranshu Chaturvedi, Shilan He, Han Chen, Gagandeep Singh, Volodymyr V. Kindratenko, Eliu A. Huerta, Kibaek Kim, Ravi K. Madduri:
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler. ICLR 2024 - [c8]Grant Wilkins, Sheng Di, Jon C. Calhoun, Zilinghan Li, Kibaek Kim, Robert Underwood, Richard Mortier, Franck Cappello:
FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications. IPDPS (Workshops) 2024: 1187-1188 - [c7]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 - [i21]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) - [i20]Zilinghan Li, Shilan He, Pranshu Chaturvedi, Volodymyr V. Kindratenko, Eliu A. Huerta, Kibaek Kim, Ravi K. Madduri:
Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources - A Case Study on Federated Fine-tuning of LLaMA 2. CoRR abs/2402.12271 (2024) - [i19]Guangji Bai, Yijiang Li, Chen Ling, Kibaek Kim, Liang Zhao:
Gradient-Free Adaptive Global Pruning for Pre-trained Language Models. CoRR abs/2402.17946 (2024) - [i18]Shourya Bose, Yu Zhang, Kibaek Kim:
Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers. CoRR abs/2404.01517 (2024) - [i17]Charikleia Iakovidou, Kibaek Kim:
Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays. CoRR abs/2405.10123 (2024) - [i16]Hendrik F. Hamann, Thomas Brunschwiler, Blazhe Gjorgiev, Leonardo S. A. Martins, Alban Puech, Anna Varbella, Jonas Weiss, Juan Bernabé-Moreno, Alexandre Blondin Massé, Seong Choi, Ian T. Foster, Bri-Mathias S. Hodge, Rishabh Jain, Kibaek Kim, Vincent Mai, François Mirallès, Martin De Montigny, Octavio Ramos-Leaños, Hussein Suprême, Le Xie, El-Nasser S. Youssef, Arnaud Zinflou, Alexander J. Belvi, Ricardo J. Bessa, Bishnu Prasad Bhattari, Johannes Schmude, Stanislav Sobolevsky:
A Perspective on Foundation Models for the Electric Power Grid. CoRR abs/2407.09434 (2024) - [i15]Zilinghan Li, Shilan He, Ze Yang, Minseok Ryu, Kibaek Kim, Ravi K. Madduri:
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework. CoRR abs/2409.11585 (2024) - [i14]Ravi K. Madduri, Zilinghan Li, Tarak Nandi, Kibaek Kim, Minseok Ryu, Alex Rodriguez:
Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare System. CoRR abs/2409.19756 (2024) - 2023
- [c6]Zilinghan Li, Shilan He, Pranshu Chaturvedi, Trung-Hieu Hoang, Minseok Ryu, Eliu A. Huerta, Volodymyr V. Kindratenko, Jordan D. Fuhrman, Maryellen L. Giger, Ryan Chard, Kibaek Kim, Ravi K. Madduri:
APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service. e-Science 2023: 1-4 - [i13]Minseok Ryu, Kibaek Kim:
Differentially Private Distributed Convex Optimization. CoRR abs/2302.14514 (2023) - [i12]Zilinghan Li, Shilan He, Pranshu Chaturvedi, Trung-Hieu Hoang, Minseok Ryu, Eliu A. Huerta, Volodymyr V. Kindratenko, Jordan D. Fuhrman, Maryellen L. Giger, Ryan Chard, Kibaek Kim, Ravi K. Madduri:
APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service. CoRR abs/2308.08786 (2023) - [i11]Shourya Bose, Kibaek Kim:
Federated Short-Term Load Forecasting with Personalization Layers for Heterogeneous Clients. CoRR abs/2309.13194 (2023) - [i10]Zilinghan Li, Pranshu Chaturvedi, Shilan He, Han Chen, Gagandeep Singh, Volodymyr V. Kindratenko, Eliu A. Huerta, Kibaek Kim, Ravi K. Madduri:
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler. CoRR abs/2309.14675 (2023) - [i9]Shourya Bose, Yu Zhang, Kibaek Kim:
Privacy-Preserving Load Forecasting via Personalized Model Obfuscation. CoRR abs/2312.00036 (2023) - [i8]Trung-Hieu Hoang, Jordan D. Fuhrman, Ravi K. Madduri, Miao Li, Pranshu Chaturvedi, Zilinghan Li, Kibaek Kim, Minseok Ryu, Ryan Chard, Eliu A. Huerta, Maryellen L. Giger:
Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx. CoRR abs/2312.08701 (2023) - [i7]Grant Wilkins, Sheng Di, Jon C. Calhoun, Kibaek Kim, Robert Underwood, Richard Mortier, Franck Cappello:
Efficient Communication in Federated Learning Using Floating-Point Lossy Compression. CoRR abs/2312.13461 (2023) - 2022
- [j8]Kibaek Kim, Brian C. Dandurand:
Scalable branching on dual decomposition of stochastic mixed-integer programming problems. Math. Program. Comput. 14(1): 1-41 (2022) - [c5]Youngdae Kim, Kibaek Kim:
Accelerated Computation and Tracking of AC Optimal Power Flow Solutions Using GPUs. ICPP Workshops 2022: 19:1-19:8 - [c4]Minseok Ryu, Youngdae Kim, Kibaek Kim, Ravi K. Madduri:
APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning. IPDPS Workshops 2022: 1074-1083 - [i6]Minseok Ryu, Youngdae Kim, Kibaek Kim, Ravi K. Madduri:
APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning. CoRR abs/2202.03672 (2022) - [i5]Minseok Ryu, Kibaek Kim:
Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates. CoRR abs/2202.09409 (2022) - 2021
- [j7]Brian C. Dandurand, Kibaek Kim, Sven Leyffer:
A Bilevel Approach for Identifying the Worst Contingencies for Nonconvex Alternating Current Power Systems. SIAM J. Optim. 31(1): 702-726 (2021) - [i4]Minseok Ryu, Kibaek Kim:
Differentially Private Federated Learning via Inexact ADMM. CoRR abs/2106.06127 (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]Kibaek Kim, Cosmin G. Petra, Victor M. Zavala:
An Asynchronous Bundle-Trust-Region Method for Dual Decomposition of Stochastic Mixed-Integer Programming. SIAM J. Optim. 29(1): 318-342 (2019) - 2018
- [j5]Kibaek Kim, Victor M. Zavala:
Algorithmic innovations and software for the dual decomposition method applied to stochastic mixed-integer programs. Math. Program. Comput. 10(2): 225-266 (2018) - 2017
- [j4]Victor M. Zavala, Kibaek Kim, Mihai Anitescu, John R. Birge:
A Stochastic Electricity Market Clearing Formulation with Consistent Pricing Properties. Oper. Res. 65(3): 557-576 (2017) - 2016
- [i1]Kibaek Kim, Fan Yang, Victor M. Zavala, Andrew A. Chien:
Data Centers as Dispatchable Loads to Harness Stranded Power. CoRR abs/1606.00350 (2016) - 2015
- [j3]Kibaek Kim, Sanjay Mehrotra:
A Two-Stage Stochastic Integer Programming Approach to Integrated Staffing and Scheduling with Application to Nurse Management. Oper. Res. 63(6): 1431-1451 (2015) - 2014
- [j2]Kibaek Kim, Gwanggil Jeon, Jechang Jeong:
Adaptive Intra Prediction Mode Signaling Approach in H.264/AVC. IEICE Trans. Commun. 97-B(9): 1990-1999 (2014) - [j1]Kibaek Kim, Gwanggil Jeon, Jechang Jeong:
Piecewise DC prediction in HEVC. Signal Process. Image Commun. 29(9): 945-950 (2014) - [c3]Gwanggil Jeon, Kibaek Kim, Jechang Jeong:
Improved Residual DPCM for HEVC Lossless Coding. SIBGRAPI 2014: 95-102 - [c2]Kibaek Kim, Gwanggil Jeon, Jechang Jeong:
Improvement of Implicit Residual DPCM for HEVC. SITIS 2014: 652-658 - 2012
- [c1]Jae-Hun Kim, Kibaek Kim, Janghyeok Yun, Jechang Jeong, Gwanggil Jeon:
Advanced Hybrid Interpolation Based on Edge Direction Extracted from the DCT Coefficient Distribution. SITIS 2012: 918-924
Coauthor Index
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last updated on 2024-10-21 21:30 CEST by the dblp team
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