Jongho Park

According to our database, Jongho Park authored at least 24 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Additive Schwarz Methods for Fourth-Order Variational Inequalities.

Jongho Park

J. Sci. Comput., December, 2024

Parareal Neural Networks Emulating a Parallel-in-Time Algorithm.

Youngkyu Lee, Jongho Park, Chang-Ock Lee

IEEE Trans. Neural Networks Learn. Syst., May, 2024

Additive Schwarz Methods for Semilinear Elliptic Problems with Convex Energy Functionals: Convergence Rate Independent of Nonlinearity.

Jongho Park

SIAM J. Sci. Comput., 2024

Randomized greedy algorithms for neural network optimization.

Jongho Park, Jinchao Xu, Xiaofeng Xu

CoRR, 2024

Two-level overlapping Schwarz preconditioners with universal coarse spaces for 2mth-order elliptic problems.

Jongho Park

CoRR, 2024

2023

An Optimized Dynamic Mode Decomposition Model Robust to Multiplicative Noise.

Minwoo Lee, Jongho Park

SIAM J. Appl. Dyn. Syst., March, 2023

Balanced Group Convolution: An Improved Group Convolution Based on Approximability Estimates.

Youngkyu Lee, Jongho Park, Chang-Ock Lee

CoRR, 2023

DualFL: A Duality-based Federated Learning Algorithm with Communication Acceleration in the General Convex Regime.

Jongho Park, Jinchao Xu

CoRR, 2023

A numerically efficient output-only system-identification framework for stochastically forced self-sustained oscillators.

Minwoo Lee, Kyu-Tae Kim, Jongho Park

CoRR, 2023

Preconditioning for finite element methods with strain smoothing.

Chaemin Lee, Jongho Park

Comput. Math. Appl., 2023

2022

Two-level group convolution.

Youngkyu Lee, Jongho Park, Chang-Ock Lee

Neural Networks, 2022

A neuron-wise subspace correction method for the finite neuron method.

Jongho Park, Jinchao Xu, Xiaofeng Xu

CoRR, 2022

Additive Schwarz methods for convex optimization with backtracking.

Jongho Park

Comput. Math. Appl., 2022

Fast gradient methods for uniformly convex and weakly smooth problems.

Jongho Park

Adv. Comput. Math., 2022

2021

Accelerated Additive Schwarz Methods for Convex Optimization with Adaptive Restart.

Jongho Park

J. Sci. Comput., 2021

A variational framework for the strain-smoothed element method.

Chaemin Lee, Jongho Park

Comput. Math. Appl., 2021

2020

Additive Schwarz Methods for Convex Optimization as Gradient Methods.

Jongho Park

SIAM J. Numer. Anal., 2020

Correction to: A dual iterative substructuring method with a small penalty parameter.

Chang-Ock Lee, Eun-Hee Park, Jongho Park

CoRR, 2020

An Overlapping Domain Decomposition Framework without Dual Formulation for Variational Imaging Problems.

Jongho Park

CoRR, 2020

2019

A Finite Element Approach for the Dual Rudin-Osher-Fatemi Model and Its Nonoverlapping Domain Decomposition Methods.

Chang-Ock Lee, Eun-Hee Park, Jongho Park

SIAM J. Sci. Comput., 2019

Fast Nonoverlapping Block Jacobi Method for the Dual Rudin-Osher-Fatemi Model.

Chang-Ock Lee, Jongho Park

SIAM J. Imaging Sci., 2019

A Finite Element Nonoverlapping Domain Decomposition Method with Lagrange Multipliers for the Dual Total Variation Minimizations.

Chang-Ock Lee, Jongho Park

J. Sci. Comput., 2019

Domain Decomposition Methods Using Dual Conversion for the Total Variation Minimization with $$L^1$$ L 1 Fidelity Term.

Chang-Ock Lee, Changmin Nam, Jongho Park

J. Sci. Comput., 2019

Pseudo-linear Convergence of an Additive Schwarz Method for Dual Total Variation Minimization.

Jongho Park

CoRR, 2019