6 citations · 8 across the 5 of their papers we have counts for
5 papers
Parameter-Free Accelerated Quasi-Newton Method for Nonconvex Optimization
Naoki Marumo
We propose a quasi-Newton-type method for nonconvex optimization with Lipschitz continuous gradients and Hessians. The algorithm finds an -stationary point within $\ma…
Heavy-ball Differential Equation Achieves Convergence for Nonconvex Functions
Kaito Okamura, Naoki Marumo, Akiko Takeda
First-order optimization methods for nonconvex functions with Lipschitz continuous gradient and Hessian have been extensively studied. State-of-the-art methods for finding an $\var…
Modelling the discretization error of initial value problems using the Wishart distribution
Naoki Marumo, Takeru Matsuda, Yuto Miyatake
This paper presents a new discretization error quantification method for the numerical integration of ordinary differential equations. The error is modelled by using the Wishart di…
Universal heavy-ball method for nonconvex optimization under Hölder continuous Hessians
Naoki Marumo, Akiko Takeda
We propose a new first-order method for minimizing nonconvex functions with Lipschitz continuous gradients and Hölder continuous Hessians. The proposed algorithm is a heavy-ball me…
Parameter-free accelerated gradient descent for nonconvex minimization
Naoki Marumo, Akiko Takeda
We propose a new first-order method for minimizing nonconvex functions with a Lipschitz continuous gradient and Hessian. The proposed method is an accelerated gradient descent with…