| A simple and fast algorithm for L1-norm kernel PCA C Kim, D Klabjan IEEE transactions on pattern analysis and machine intelligence 42 (8), 1842-1855, 2019 | 74 | 2019 |
| Graph convolutional neural networks for optimal load shedding under line contingency C Kim, K Kim, P Balaprakash, M Anitescu 2019 ieee power & energy society general meeting (pesgm), 1-5, 2019 | 63 | 2019 |
| Stochastic variance-reduced algorithms for PCA with arbitrary mini-batch sizes C Kim, D Klabjan International Conference on Artificial Intelligence and Statistics, 4302-4312, 2020 | 8 | 2020 |
| Optimal expediting policies for an inventory system with stochastic lead time under radio frequency identification C Kim, D Klabjan, D Simchi-Levi Working paper. Massachusetts Institute of Technology, 2007 | 5 | 2007 |
| Stochastic variance-reduced heavy ball power iteration C Kim, D Klabjan arXiv preprint arXiv:1901.08179, 2019 | 3 | 2019 |
| Solution approaches to linear fractional programming and its stochastic generalizations using second order cone approximations C Kim, S Mehrotra SIAM Journal on Optimization 31 (1), 945-971, 2021 | 2 | 2021 |
| Scale invariant power iteration C Kim, Y Kim, D Klabjan arXiv preprint arXiv:1905.09882, 2019 | 2 | 2019 |
| An algorithm for stochastic convex-concave fractional programs with applications to production efficiency and equitable resource allocation S Dey, C Kim, S Mehrotra European Journal of Operational Research 315 (3), 980-990, 2024 | | 2024 |
| Stochastic Scale Invariant Power Iteration for KL-divergence Nonnegative Matrix Factorization C Kim, Y Kim, D Klabjan arXiv preprint arXiv:2304.11268, 2023 | | 2023 |
| Scale invariant power iteration C Kim, Y Kim, D Klabjan Journal of Machine Learning Research 24 (321), 1-47, 2023 | | 2023 |
| Optimization Methods for Scale Invariant Problems in Machine Learning C Kim Northwestern University, 2020 | | 2020 |
