4 citations · 5 across the 10 of their papers we have counts for
10 papers
Parameter-Free Cubic-Regularized Newton Method: Sharp Complexity and Generalized Smoothness
Shaoying Fang, Naoki Marumo, Akiko Takeda
We analyze a variant of the cubic-regularized Newton method for nonconvex optimization. This variant is parameter-free in that it requires no prior knowledge of problem-dependent p…
A General Recipe for Parameter-Free Nonconvex Optimization via Higher-Order Regularization
Naoki Marumo, Akiko Takeda
We develop a systematic framework for constructing parameter-free algorithms for smooth nonconvex optimization. The framework is based on higher-order regularization: each step is…
Practical Regularized Quasi-Newton Methods with Inexact Function Values
Hiroki Hamaguchi, Naoki Marumo, Akiko Takeda
Many practical optimization problems involve objective function values that are corrupted by unavoidable numerical errors. In smooth nonconvex optimization, quasi-Newton methods co…
Complexity and convergence analysis of a single-loop SDCAM for Lipschitz composite optimization and beyond
Hao Zhang, Naoki Marumo, Ting Kei Pong +1
We develop and analyze a single-loop algorithm for minimizing the sum of a Lipschitz differentiable function , a prox-friendly proper closed function (with a closed domain o…
A Regression-Based Prediction-Correction Method for Stochastic Time-Varying Optimization Problems
Tomoya Kamijima, Naoki Marumo, Akiko Takeda
In many real-world applications, optimization problems evolve continuously over time and are often subject to stochastic noise. We consider a stochastic time-varying optimization p…
On the equivalence of a Hessian-free inequality and Lipschitz continuous Hessian
Radu I. Boţ, Minh N. Dao, Tianxiang Liu +2
It is known that if a twice differentiable function has a Lipschitz continuous Hessian, then its gradients satisfy a Jensen-type inequality. In particular, this inequality is Hessi…
A Simple yet Highly Accurate Prediction-Correction Algorithm for Time-Varying Optimization
Tomoya Kamijima, Naoki Marumo, Akiko Takeda
This paper proposes a simple yet highly accurate prediction-correction algorithm, SHARP, for unconstrained time-varying optimization problems. Its prediction is based on an extrapo…
Initial Placement for Fruchterman--Reingold Force Model With Coordinate Newton Direction
Hiroki Hamaguchi, Naoki Marumo, Akiko Takeda
The Fruchterman--Reingold (FR) force model is widely used in force-directed graph drawing, and multilevel approaches such as sfdp in Graphviz scale these methods effectively. A cru…
Faster computation of nonstabilizerness
Hiroki Hamaguchi, Kou Hamada, Naoki Marumo +1
The characterization of nonstabilizerness is fruitful due to its application in gate synthesis and classical simulation. In particular, the resource monotone called the stabilizer…
Optimal Transport with Cyclic Symmetry
Shoichiro Takeda, Yasunori Akagi, Naoki Marumo +1
We propose novel fast algorithms for optimal transport (OT) utilizing a cyclic symmetry structure of input data. Such OT with cyclic symmetry appears universally in various real-wo…