Ernest K. Ryu

Orcid: 0000-0001-6820-9095

According to our database1, Ernest K. Ryu authored at least 43 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Publisher Correction: Branch-and-bound performance estimation programming: a unified methodology for constructing optimal optimization methods.
Math. Program., March, 2024

Branch-and-bound performance estimation programming: a unified methodology for constructing optimal optimization methods.
Math. Program., March, 2024

Optimal First-Order Algorithms as a Function of Inequalities.
J. Mach. Learn. Res., 2024

Task Diversity Shortens the ICL Plateau.
CoRR, 2024

Encryption-Friendly LLM Architecture.
CoRR, 2024

Gradient-free Decoder Inversion in Latent Diffusion Models.
CoRR, 2024

Deflated Dynamics Value Iteration.
CoRR, 2024

Simple Drop-in LoRA Conditioning on Attention Layers Will Improve Your Diffusion Model.
CoRR, 2024

Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

LoRA Training in the NTK Regime has No Spurious Local Minima.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Image Clustering Conditioned on Text Criteria.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Accelerating Value Iteration with Anchoring.
CoRR, 2023

Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Continuous-time Analysis of Anchor Acceleration.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Accelerated Infeasibility Detection of Constrained Optimization and Fixed-Point Iterations.
Proceedings of the International Conference on Machine Learning, 2023

Rotation and Translation Invariant Representation Learning with Implicit Neural Representations.
Proceedings of the International Conference on Machine Learning, 2023

2022
Scaled relative graphs: nonexpansive operators via 2D Euclidean geometry.
Math. Program., 2022

Continuous-Time Analysis of Accelerated Gradient Methods via Conservation Laws in Dilated Coordinate Systems.
Proceedings of the International Conference on Machine Learning, 2022

Exact Optimal Accelerated Complexity for Fixed-Point Iterations.
Proceedings of the International Conference on Machine Learning, 2022

Neural Tangent Kernel Analysis of Deep Narrow Neural Networks.
Proceedings of the International Conference on Machine Learning, 2022

Robust Probabilistic Time Series Forecasting.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Decentralized Proximal Gradient Algorithms With Linear Convergence Rates.
IEEE Trans. Autom. Control., 2021

WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points.
CoRR, 2021

A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm.
Proceedings of the 38th International Conference on Machine Learning, 2021

WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Splitting with Near-Circulant Linear Systems: Applications to Total Variation CT and PET.
SIAM J. Sci. Comput., 2020

Operator Splitting Performance Estimation: Tight Contraction Factors and Optimal Parameter Selection.
SIAM J. Optim., 2020

Linear convergence of cyclic SAGA.
Optim. Lett., 2020

Uniqueness of DRS as the 2 operator resolvent-splitting and impossibility of 3 operator resolvent-splitting.
Math. Program., 2020

Finding the Forward-Douglas-Rachford-Forward Method.
J. Optim. Theory Appl., 2020

Scaled Relative Graph of Normal Matrices.
CoRR, 2020

2019
A new use of Douglas-Rachford splitting for identifying infeasible, unbounded, and pathological conic programs.
Math. Program., 2019

ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems and GANs.
CoRR, 2019

Douglas-Rachford splitting and ADMM for pathological convex optimization.
Comput. Optim. Appl., 2019

Plug-and-Play Methods Provably Converge with Properly Trained Denoisers.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Vector and Matrix Optimal Mass Transport: Theory, Algorithm, and Applications.
SIAM J. Sci. Comput., 2018

Unbalanced and Partial L<sub>1</sub> Monge-Kantorovich Problem: A Scalable Parallel First-Order Method.
J. Sci. Comput., 2018

A Parallel Method for Earth Mover's Distance.
J. Sci. Comput., 2018

2017
A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs.
CoRR, 2017

2015
Extensions of Gauss Quadrature Via Linear Programming.
Found. Comput. Math., 2015

2012
Stochastic Kronecker Graph on Vertex-Centric BSP
CoRR, 2012


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