| Primer on monotone operator methods EK Ryu, S Boyd Appl. comput. math 15 (1), 3-43, 2016 | 332 | 2016 |
| Plug-and-play methods provably converge with properly trained denoisers E Ryu, J Liu, S Wang, X Chen, Z Wang, W Yin International Conference on Machine Learning, 5546-5557, 2019 | 239 | 2019 |
| Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices H Monajemi, S Jafarpour, M Gavish, Stat 330/CME 362 Collaboration, ... Proceedings of the National Academy of Sciences 110 (4), 1181-1186, 2013 | 111 | 2013 |
| Structural characterization of unsaturated phosphatidylcholines using traveling wave ion mobility spectrometry HI Kim, H Kim, ES Pang, EK Ryu, LW Beegle, JA Loo, WA Goddard, ... Analytical chemistry 81 (20), 8289-8297, 2009 | 101 | 2009 |
| A parallel method for earth mover’s distance W Li, EK Ryu, S Osher, W Yin, W Gangbo Journal of Scientific Computing 75 (1), 182-197, 2018 | 89 | 2018 |
| Decentralized proximal gradient algorithms with linear convergence rates SA Alghunaim, EK Ryu, K Yuan, AH Sayed IEEE Transactions on Automatic Control 66 (6), 2787-2794, 2020 | 81 | 2020 |
| Operator splitting performance estimation: Tight contraction factors and optimal parameter selection EK Ryu, AB Taylor, C Bergeling, P Giselsson SIAM Journal on Optimization 30 (3), 2251-2271, 2020 | 75 | 2020 |
| Large-Scale Convex Optimization: Algorithms & Analyses via Monotone Operators EK Ryu, W Yin Cambridge University Press, 2022 | 69 | 2022 |
| Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O (1/k^ 2) Rate on Squared Gradient Norm TH Yoon, EK Ryu International Conference on Machine Learning, 12098-12109, 2021 | 68 | 2021 |
| Extensions of Gauss quadrature via linear programming EK Ryu, SP Boyd Foundations of Computational Mathematics 15 (4), 953-971, 2015 | 66 | 2015 |
| Stochastic proximal iteration: a non-asymptotic improvement upon stochastic gradient descent EK Ryu, S Boyd Author website, early draft, 2014 | 48 | 2014 |
| Adaptive importance sampling via stochastic convex programming EK Ryu, SP Boyd arXiv preprint arXiv:1412.4845, 2014 | 38 | 2014 |
| Finding the forward-Douglas–Rachford-forward method EK Ryu, BC Vũ Journal of Optimization Theory and Applications 184 (3), 858-876, 2020 | 37 | 2020 |
| A new use of Douglas–Rachford splitting for identifying infeasible, unbounded, and pathological conic programs Y Liu, EK Ryu, W Yin Mathematical Programming 177 (1-2), 225-253, 2019 | 34* | 2019 |
| Scaled relative graphs: Nonexpansive operators via 2D Euclidean geometry EK Ryu, R Hannah, W Yin Mathematical Programming 194 (1-2), 569-619, 2022 | 32 | 2022 |
| Risk-constrained Kelly gambling E Busseti, EK Ryu, S Boyd The Journal of Investing 25 (3), 118-134, 2016 | 31 | 2016 |
| ODE analysis of stochastic gradient methods with optimism and anchoring for minimax problems and GANs EK Ryu, K Yuan, W Yin | 29* | 2019 |
| Proximal-proximal-gradient method EK Ryu, W Yin arXiv preprint arXiv:1708.06908, 2017 | 29 | 2017 |
| Uniqueness of DRS as the 2 operator resolvent-splitting and impossibility of 3 operator resolvent-splitting EK Ryu Mathematical Programming 182 (1-2), 233-273, 2020 | 28 | 2020 |
| Vector and matrix optimal mass transport: theory, algorithm, and applications EK Ryu, Y Chen, W Li, S Osher SIAM Journal on Scientific Computing 40 (5), A3675-A3698, 2018 | 26 | 2018 |
