RV-SVM: An efficient method for learning ranking SVM H Yu, Y Kim, S Hwang Pacific-Asia Conference on Knowledge Discovery and Data Mining, 426-438, 2009 | 42 | 2009 |
An efficient method for learning nonlinear ranking SVM functions H Yu, J Kim, Y Kim, S Hwang, YH Lee Information Sciences 209, 37-48, 2012 | 35 | 2012 |
MPEC methods for bilevel optimization problems Y Kim, S Leyffer, T Munson Bilevel optimization: advances and next challenges, 2020 | 28 | 2020 |
Solving equilibrium problems using extended mathematical programming Y Kim, MC Ferris Mathematical programming computation 11, 457-501, 2019 | 22 | 2019 |
APPFL: open-source software framework for privacy-preserving federated learning M Ryu, Y Kim, K Kim, RK Madduri 2022 IEEE International Parallel and Distributed Processing Symposium …, 2022 | 19 | 2022 |
Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition Y Kim, F Pacaud, K Kim, M Anitescu arXiv preprint arXiv:2106.14995, 2021 | 16 | 2021 |
Adaptively refined dynamic program for linear spline regression N Goldberg, Y Kim, S Leyffer, TD Veselka Computational Optimization and Applications 58, 523-541, 2014 | 16 | 2014 |
A reinforcement learning approach to parameter selection for distributed optimal power flow S Zeng, A Kody, Y Kim, K Kim, DK Molzahn Electric Power Systems Research 212, 108546, 2022 | 15 | 2022 |
Exact indexing for support vector machines H Yu, I Ko, Y Kim, S Hwang, WS Han Proceedings of the 2011 ACM SIGMOD International Conference on Management of …, 2011 | 13 | 2011 |
Accelerated computation and tracking of AC optimal power flow solutions using GPUs Y Kim, K Kim Workshop Proceedings of the 51st International Conference on Parallel …, 2022 | 12 | 2022 |
Diversity and scale: genetic architecture of 2,068 traits in the VA Million Veteran Program A Verma, JE Huffman, A Rodriguez, M Conery, M Liu, YL Ho, Y Kim, ... medRxiv, 2023 | 11 | 2023 |
A real-time optimization with warm-start of multiperiod AC optimal power flows Y Kim, M Anitescu Electric Power Systems Research 189, 2020 | 8 | 2020 |
MINLP formulations for continuous piecewise linear function fitting N Goldberg, S Rebennack, Y Kim, V Krasko, S Leyffer Computational Optimization and Applications, 2021 | 7 | 2021 |
A structure-preserving pivotal method for affine variational inequalities Y Kim, O Huber, MC Ferris Mathematical Programming 168, 93-121, 2018 | 7 | 2018 |
A reinforcement learning approach to parameter selection for distributed optimization in power systems S Zeng, A Kody, Y Kim, K Kim, DK Molzahn arXiv preprint arXiv:2110.11991, 2021 | 6 | 2021 |
GPU-accelerated DNS of compressible turbulent flows Y Kim, D Ghosh, EM Constantinescu, R Balakrishnan Computers and Fluids 251, 2023 | 4 | 2023 |
iKernel: Exact indexing for support vector machines Y Kim, I Ko, WS Han, H Yu Information Sciences 257, 32-53, 2014 | 4 | 2014 |
Escaping a dominance region at minimum cost Y Kim, G You, S Hwang International Conference on Database and Expert Systems Applications, 800-807, 2008 | 4 | 2008 |
Solving Stochastic Dynamic Programming Problems: A Mixed Complementarity Approach W Chang, MC Ferris, Y Kim, TF Rutherford Computational Economics, 1-31, 2019 | 3 | 2019 |
A Globally Convergent Distributed Jacobi Scheme for Block-Structured Nonconvex Constrained Optimization Problems A Subramanyam, Y Kim, M Schanen, F Pacaud, M Anitescu arXiv preprint arXiv:2112.09027, 2021 | 2 | 2021 |