Kibaek Kim

IEEE Trans. Smart Grid, September, 2024

Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources: A Case Study on Federated Fine-Tuning of LLaMA 2.

[BibT_eX]

[DOI]

Zilinghan Li

Shilan He

Pranshu Chaturvedi

Volodymyr V. Kindratenko

Eliu A. Huerta

Ravi K. Madduri

Comput. Sci. Eng., 2024

From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption.

[BibT_eX]

[DOI]

CoRR, 2024

FedSpaLLM: Federated Pruning of Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare System.

[BibT_eX]

[DOI]

CoRR, 2024

Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework.

[BibT_eX]

[DOI]

CoRR, 2024

A Perspective on Foundation Models for the Electric Power Grid.

[BibT_eX]

[DOI]

CoRR, 2024

Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays.

[BibT_eX]

[DOI]

Charikleia Iakovidou

CoRR, 2024

Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers.

[BibT_eX]

[DOI]

Shourya Bose

Yu Zhang

CoRR, 2024

Gradient-Free Adaptive Global Pruning for Pre-trained Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

QCQP-Net: Reliably learning feasible alternating current optimal power flow solutions under constraints.

[BibT_eX]

[DOI]

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler.

[BibT_eX]

[DOI]

Volodymyr V. Kindratenko

Eliu A. Huerta

Ravi K. Madduri

Proceedings of the Twelfth International Conference on Learning Representations, 2024

FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications.

[BibT_eX]

[DOI]

Proceedings of the 44th IEEE International Conference on Distributed Computing Systems, 2024

2023

Efficient Communication in Federated Learning Using Floating-Point Lossy Compression.

[BibT_eX]

[DOI]

CoRR, 2023

Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx.

[BibT_eX]

[DOI]

CoRR, 2023

Privacy-Preserving Load Forecasting via Personalized Model Obfuscation.

[BibT_eX]

[DOI]

Shourya Bose

Yu Zhang

CoRR, 2023

Federated Short-Term Load Forecasting with Personalization Layers for Heterogeneous Clients.

[BibT_eX]

[DOI]

Shourya Bose

CoRR, 2023

Differentially Private Distributed Convex Optimization.

[BibT_eX]

[DOI]

Minseok Ryu

CoRR, 2023

APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service.

[BibT_eX]

[DOI]

Volodymyr V. Kindratenko

Proceedings of the 19th IEEE International Conference on e-Science, 2023

2022

Scalable branching on dual decomposition of stochastic mixed-integer programming problems.

[BibT_eX]

[DOI]

Brian C. Dandurand

Math. Program. Comput., 2022

Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates.

[BibT_eX]

[DOI]

Minseok Ryu

CoRR, 2022

APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Accelerated Computation and Tracking of AC Optimal Power Flow Solutions Using GPUs.

[BibT_eX]

[DOI]

Youngdae Kim

Proceedings of the Workshop Proceedings of the 51st International Conference on Parallel Processing, 2022

2021

A Bilevel Approach for Identifying the Worst Contingencies for Nonconvex Alternating Current Power Systems.

[BibT_eX]

[DOI]

Brian C. Dandurand

Sven Leyffer

SIAM J. Optim., 2021

A Reinforcement Learning Approach to Parameter Selection for Distributed Optimization in Power Systems.

[BibT_eX]

[DOI]

CoRR, 2021

Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition.

[BibT_eX]

[DOI]

CoRR, 2021

Differentially Private Federated Learning via Inexact ADMM.

[BibT_eX]

[DOI]

Minseok Ryu

CoRR, 2021

2019

An Asynchronous Bundle-Trust-Region Method for Dual Decomposition of Stochastic Mixed-Integer Programming.

[BibT_eX]

[DOI]

Cosmin G. Petra

Victor M. Zavala

SIAM J. Optim., 2019

2018

Algorithmic innovations and software for the dual decomposition method applied to stochastic mixed-integer programs.

[BibT_eX]

[DOI]

Victor M. Zavala

Math. Program. Comput., 2018

2017

A Stochastic Electricity Market Clearing Formulation with Consistent Pricing Properties.

[BibT_eX]

[DOI]

Oper. Res., 2017

2016

Data Centers as Dispatchable Loads to Harness Stranded Power.

[BibT_eX]

[DOI]

CoRR, 2016

2015

A Two-Stage Stochastic Integer Programming Approach to Integrated Staffing and Scheduling with Application to Nurse Management.

[BibT_eX]

[DOI]

Sanjay Mehrotra

Oper. Res., 2015

2014

Piecewise DC prediction in HEVC.

[BibT_eX]

[DOI]

Signal Process. Image Commun., 2014

Adaptive Intra Prediction Mode Signaling Approach in H.264/AVC.

[BibT_eX]

[DOI]

IEICE Trans. Commun., 2014

Improvement of Implicit Residual DPCM for HEVC.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Signal-Image Technology and Internet-Based Systems, 2014

Improved Residual DPCM for HEVC Lossless Coding.

[BibT_eX]

[DOI]