most citedSparse optimal stochastic control

16 citations · 41 across the 9 of their papers we have counts for

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math.OC20222 cited

Matrix Pontryagin principle approach to controllability metrics maximization under sparsity constraints

Tomofumi Ohtsuka, Takuya Ikeda, Kenji Kashima

Controllability maximization problem under sparsity constraints is a node selection problem that selects inputs that are effective for control in order to minimize the energy to co…

math.OC2022

Sinkhorn MPC: Model predictive optimal transport over dynamical systems

Kaito Ito, Kenji Kashima

We consider the optimal control problem of steering an agent population to a desired distribution over an infinite horizon. This is an optimal transport problem over a dynamical sy…

math.OC202116 cited

Sparse optimal stochastic control

Kaito Ito, Takuya Ikeda, Kenji Kashima

In this paper, we investigate a sparse optimal control of continuous-time stochastic systems. We adopt the dynamic programming approach and analyze the optimal control via the valu…

math.OC2021

Multiple sparsity constrained control node scheduling with application to rebalancing of mobility networks

Takuya Ikeda, Kazunori Sakurama, Kenji Kashima

This paper treats an optimal scheduling problem of control nodes in networked systems. We newly introduce both the L0 and l0 constraints on control inputs to extract a time-varying…

math.OC202112 cited

Structured Hammerstein-Wiener Model Learning for Model Predictive Control

Ryuta Moriyasu, Taro Ikeda, Sho Kawaguchi +1

This paper aims to improve the reliability of optimal control using models constructed by machine learning methods. Optimal control problems based on such models are generally non-…

math.OC20218 cited

Bayesian Differential Privacy for Linear Dynamical Systems

Genki Sugiura, Kaito Ito, Kenji Kashima

Differential privacy is a privacy measure based on the difficulty of discriminating between similar input data. In differential privacy analysis, similar data usually implies that…