Stochastic Kronecker Graph on Vertex-Centric BSP - Ernest K. Ryu; Sean Choi (CoRR, 2012)

Extensions of Gauss Quadrature Via Linear Programming. - Ernest K. Ryu; Stephen P. Boyd (Found. Comput. Math., 2015)

A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs. - Yanli Liu 003; Ernest K. Ryu; Wotao Yin (CoRR, 2017)

A Parallel Method for Earth Mover's Distance. - Wuchen Li; Ernest K. Ryu; Stanley J. Osher; Wotao Yin; Wilfrid Gangbo (J. Sci. Comput., 2018)

Unbalanced and Partial L1 Monge-Kantorovich Problem: A Scalable Parallel First-Order Method. - Ernest K. Ryu; Wuchen Li; Penghang Yin; Stanley J. Osher (J. Sci. Comput., 2018)

Vector and Matrix Optimal Mass Transport: Theory, Algorithm, and Applications. - Ernest K. Ryu; Yongxin Chen; Wuchen Li; Stanley J. Osher (SIAM J. Sci. Comput., 2018)

Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. - Ernest K. Ryu; Jialin Liu 003; Sicheng Wang 003; Xiaohan Chen; Zhangyang Wang; Wotao Yin (ICML, 2019)

Douglas-Rachford splitting and ADMM for pathological convex optimization. - Ernest K. Ryu; Yanli Liu 003; Wotao Yin (Comput. Optim. Appl., 2019)

ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems and GANs. - Ernest K. Ryu; Kun Yuan 001; Wotao Yin (CoRR, 2019)

A new use of Douglas-Rachford splitting for identifying infeasible, unbounded, and pathological conic programs. - Yanli Liu 003; Ernest K. Ryu; Wotao Yin (Math. Program., 2019)

Scaled Relative Graph of Normal Matrices. - Xinmeng Huang; Ernest K. Ryu; Wotao Yin (CoRR, 2020)

Finding the Forward-Douglas-Rachford-Forward Method. - Ernest K. Ryu; Bang Công Vu (J. Optim. Theory Appl., 2020)

Uniqueness of DRS as the 2 operator resolvent-splitting and impossibility of 3 operator resolvent-splitting. - Ernest K. Ryu (Math. Program., 2020)

Linear convergence of cyclic SAGA. - Youngsuk Park; Ernest K. Ryu (Optim. Lett., 2020)

Operator Splitting Performance Estimation: Tight Contraction Factors and Optimal Parameter Selection. - Ernest K. Ryu; Adrien B. Taylor; Carolina Bergeling; Pontus Giselsson (SIAM J. Optim., 2020)

Splitting with Near-Circulant Linear Systems: Applications to Total Variation CT and PET. - Ernest K. Ryu; Seyoon Ko; Joong-Ho Won (SIAM J. Sci. Comput., 2020)

WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points. - Albert No; Taeho Yoon; Sehyun Kwon; Ernest K. Ryu (ICML, 2021)

Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm. - Taeho Yoon; Ernest K. Ryu (ICML, 2021)

A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast. - Jongmin Lee; Chanwoo Park; Ernest K. Ryu (NeurIPS, 2021)

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates. - Sulaiman A. Alghunaim; Ernest K. Ryu; Kun Yuan 001; Ali H. Sayed (IEEE Trans. Autom. Control., 2021)

Robust Probabilistic Time Series Forecasting. - Taeho Yoon; Youngsuk Park; Ernest K. Ryu; Yuyang Wang 001 (AISTATS, 2022)

Neural Tangent Kernel Analysis of Deep Narrow Neural Networks. - Jongmin Lee; Joo Young Choi; Ernest K. Ryu; Albert No (ICML, 2022)

Exact Optimal Accelerated Complexity for Fixed-Point Iterations. - Jisun Park 003; Ernest K. Ryu (ICML, 2022)

Continuous-Time Analysis of Accelerated Gradient Methods via Conservation Laws in Dilated Coordinate Systems. - Jaewook J. Suh; Gyumin Roh; Ernest K. Ryu (ICML, 2022)

Scaled relative graphs: nonexpansive operators via 2D Euclidean geometry. - Ernest K. Ryu; Robert Hannah; Wotao Yin (Math. Program., 2022)

Rotation and Translation Invariant Representation Learning with Implicit Neural Representations. - Sehyun Kwon; Joo Young Choi; Ernest K. Ryu (ICML, 2023)

Accelerated Infeasibility Detection of Constrained Optimization and Fixed-Point Iterations. - Jisun Park 003; Ernest K. Ryu (ICML, 2023)

Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value. - Jaeyeon Kim; Asuman E. Ozdaglar; Chanwoo Park; Ernest K. Ryu (NeurIPS, 2023)

Accelerating Value Iteration with Anchoring. - Jongmin Lee; Ernest K. Ryu (NeurIPS, 2023)

Continuous-time Analysis of Anchor Acceleration. - Jaewook J. Suh; Jisun Park 003; Ernest K. Ryu (NeurIPS, 2023)

Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback. - Taeho Yoon; Kibeom Myoung; Keon Lee; Jaewoong Cho; Albert No; Ernest K. Ryu (NeurIPS, 2023)

Image Clustering Conditioned on Text Criteria. - Sehyun Kwon; Jaeseung Park; Minkyu Kim; Jaewoong Cho; Ernest K. Ryu; Kangwook Lee 001 (ICLR, 2024)

LoRA Training in the NTK Regime has No Spurious Local Minima. - Uijeong Jang; Jason D. Lee; Ernest K. Ryu (ICML, 2024)

Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique. - Taeho Yoon; Jaeyeon Kim; Jaewook J. Suh; Ernest K. Ryu (ICML, 2024)

Optimization Algorithm Design via Electric Circuits. - Stephen Boyd; Tetiana Parshakova; Ernest K. Ryu; Jaewook J. Suh (NeurIPS, 2024)

Gradient-free Decoder Inversion in Latent Diffusion Models. - Seongmin Hong; Suh Yoon Jeon; Kyeonghyun Lee; Ernest K. Ryu; Se Young Chun (NeurIPS, 2024)

Task Diversity Shortens the ICL Plateau. - Jaeyeon Kim; Sehyun Kwon; Joo Young Choi; Jongho Park; Jaewoong Cho; Jason D. Lee; Ernest K. Ryu (CoRR, 2024)

Optimization Algorithm Design via Electric Circuits. - Stephen P. Boyd; Tetiana Parshakova; Ernest K. Ryu; Jaewook J. Suh (CoRR, 2024)

Numerical Analysis of HiPPO-LegS ODE for Deep State Space Models. - Jaesung R. Park; Jaewook J. Suh; Ernest K. Ryu (CoRR, 2024)

Optimal First-Order Algorithms as a Function of Inequalities. - Chanwoo Park; Ernest K. Ryu (J. Mach. Learn. Res., 2024)

Simple Drop-in LoRA Conditioning on Attention Layers Will Improve Your Diffusion Model. - Joo Young Choi; Jaesung R. Park; Inkyu Park; Jaewoong Cho; Albert No; Ernest K. Ryu (Trans. Mach. Learn. Res., 2024)

Branch-and-bound performance estimation programming: a unified methodology for constructing optimal optimization methods. - Shuvomoy Das Gupta; Bart P. G. Van Parys; Ernest K. Ryu (Math. Program., 2024)

Publisher Correction: Branch-and-bound performance estimation programming: a unified methodology for constructing optimal optimization methods. - Shuvomoy Das Gupta; Bart P. G. Van Parys; Ernest K. Ryu (Math. Program., 2024)

Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes. - Jongmin Lee; Ernest K. Ryu (ICLR, 2025)

Encryption-Friendly LLM Architecture. - Donghwan Rho; Taeseong Kim; Minje Park; Jung Woo Kim; Hyunsik Chae; Ernest K. Ryu; Jung Hee Cheon (ICLR, 2025)

Convergence Analyses of Davis-Yin Splitting via Scaled Relative Graphs. - Jongmin Lee; Soheun Yi; Ernest K. Ryu (SIAM J. Optim., 2025)

Accelerated Minimax Algorithms Flock Together. - Taeho Yoon; Ernest K. Ryu (SIAM J. Optim., 2025)

Deflated Dynamics Value Iteration. - Jongmin Lee; Amin Rakhsha; Ernest K. Ryu; Amir-massoud Farahmand (Trans. Mach. Learn. Res., 2025)

LoRA Training Provably Converges to a Low-Rank Global Minimum or It Fails Loudly (But it Probably Won't Fail). - Junsu Kim; Jaeyeon Kim; Ernest K. Ryu (CoRR, 2025)

Decomposing Complex Visual Comprehension into Atomic Visual Skills for Vision Language Models. - Hyunsik Chae; Seungwoo Yoon; Jaden Park; Chloe Yewon Chun; Yongin Cho; Mu Cai; Yong Jae Lee; Ernest K. Ryu (CoRR, 2025)

STORK: Improving the Fidelity of Mid-NFE Sampling for Diffusion and Flow Matching Models. - Zheng Tan; Weizhen Wang; Andrea L. Bertozzi; Ernest K. Ryu (CoRR, 2025)