Escaping a Dominance Region at Minimum Cost. - Youngdae Kim; Gae-won You; Seung-won Hwang (DEXA, 2008)

Approximate Boolean + Ranking Query Answering Using Wavelets. - Youngdae Kim; Seung-won Hwang (WAIM, 2008)

RV-SVM: An Efficient Method for Learning Ranking SVM. - Hwanjo Yu; Youngdae Kim; Seung-won Hwang (PAKDD, 2009)

Ranking strategies and threats: a cost-based pareto optimization approach. - Youngdae Kim; Gae-won You; Seung-won Hwang (Distributed Parallel Databases, 2009)

Exact indexing for support vector machines. - Hwanjo Yu; Ilhwan Ko; Youngdae Kim; Seung-won Hwang; Wook-Shin Han (SIGMOD Conference, 2011)

An efficient method for learning nonlinear ranking SVM functions. - Hwanjo Yu; Jinha Kim; Youngdae Kim; Seung-won Hwang; Young Ho Lee (Inf. Sci., 2012)

Adaptively refined dynamic program for linear spline regression. - Noam Goldberg; Youngdae Kim; Sven Leyffer; Thomas D. Veselka (Comput. Optim. Appl., 2014)

iKernel: Exact indexing for support vector machines. - Youngdae Kim; Ilhwan Ko; Wook-Shin Han; Hwanjo Yu (Inf. Sci., 2014)

A structure-preserving pivotal method for affine variational inequalities. - Youngdae Kim; Olivier Huber; Michael C. Ferris (Math. Program., 2018)

Solving equilibrium problems using extended mathematical programming. - Youngdae Kim; Michael C. Ferris (Math. Program. Comput., 2019)

MINLP formulations for continuous piecewise linear function fitting. - Noam Goldberg; Steffen Rebennack; Youngdae Kim; Vitaliy Krasko; Sven Leyffer (Comput. Optim. Appl., 2021)

Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition. - Youngdae Kim; François Pacaud; Kibaek Kim; Mihai Anitescu (CoRR, 2021)

A Reinforcement Learning Approach to Parameter Selection for Distributed Optimization in Power Systems. - Sihan Zeng; Alyssa Kody; Youngdae Kim; Kibaek Kim; Daniel K. Molzahn (CoRR, 2021)

Accelerated Computation and Tracking of AC Optimal Power Flow Solutions Using GPUs. - Youngdae Kim; Kibaek Kim (ICPP Workshops, 2022)

Frequency Recovery in Power Grids using High-Performance Computing. - Vishwas Rao; Anirudh Subramanyam; Michel Schanen; Youngdae Kim; Ignas Satkauskas; Mihai Anitescu (ICPP Workshops, 2022)

APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning. - Minseok Ryu; Youngdae Kim; Kibaek Kim; Ravi K. Madduri (IPDPS Workshops, 2022)

GPU-Accelerated WENO Schemes for DNS of Compressible Turbulent Flows. - Youngdae Kim; Debojyoti Ghosh; Emil M. Constantinescu; Ramesh Balakrishnan (CoRR, 2022)

Algorithmic Read Resistance Trim for Improving Yield and Reducing Test Time in MRAM. - Daehyun Chang; Youngdae Kim; Suksoo Pyo; Shin Hun; Daesop Lee; Sohee Hwang; Jaesik Choi; Siwoong Kim (ITC, 2023)

QCQP-Net: Reliably learning feasible alternating current optimal power flow solutions under constraints. - Sihan Zeng; Youngdae Kim; Yuxuan Ren; Kibaek Kim (L4DC, 2024)

Solution polishing via path relinking for continuous black-box optimization. - Dimitri J. Papageorgiou; Jan Kronqvist; Asha Ramanujam; James Kor; Youngdae Kim; Can Li (Optim. Lett., 2025)