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ORCIDNaoki Marumo
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2020 – today
- 2024
[j6]Naoki Marumo
, Takeru Matsuda, Yuto Miyatake:
Modelling the discretization error of initial value problems using the Wishart distribution. Appl. Math. Lett. 147: 108833 (2024)- [j5]Naoki Marumo, Akiko Takeda:
Parameter-Free Accelerated Gradient Descent for Nonconvex Minimization. SIAM J. Optim. 34(2): 2093-2120 (2024) - [c9]Yasunori Akagi, Naoki Marumo, Takeshi Kurashima:
Analytically Tractable Models for Decision Making under Present Bias. AAAI 2024: 9441-9450 - [c8]Shoichiro Takeda, Yasunori Akagi, Naoki Marumo, Kenta Niwa:
Optimal Transport with Cyclic Symmetry. AAAI 2024: 15211-15221 - 2023
- [j4]Naoki Marumo, Takayuki Okuno, Akiko Takeda:
Majorization-minimization-based Levenberg-Marquardt method for constrained nonlinear least squares. Comput. Optim. Appl. 84(3): 833-874 (2023) - [j3]Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda:
MAP inference algorithms without approximation for collective graphical models on path graphs via discrete difference of convex algorithm. Mach. Learn. 112(1): 99-129 (2023) - [i6]Yasunori Akagi, Naoki Marumo, Takeshi Kurashima:
Analytically Tractable Models for Decision Making under Present Bias. CoRR abs/2302.08132 (2023) - [i5]Naoki Marumo, Takeru Matsuda, Yuto Miyatake:
Modelling the discretization error of initial value problems using the Wishart distribution. CoRR abs/2306.04084 (2023) - [i4]Shoichiro Takeda, Yasunori Akagi, Naoki Marumo, Kenta Niwa:
Optimal Transport with Cyclic Symmetry. CoRR abs/2311.13147 (2023) - 2022
- [j2]Tomoharu Iwata, Hitoshi Shimizu, Naoki Marumo:
Probabilistic Pedestrian Models for Estimating Unobserved Road Populations. IEEE Trans. Intell. Transp. Syst. 23(4): 3037-3047 (2022) - [c7]Yuya Hikima, Yasunori Akagi, Naoki Marumo, Hideaki Kim:
Online Matching with Controllable Rewards and Arrival Probabilities. IJCAI 2022: 1825-1833 - 2021
- [c6]Naoki Marumo, Atsushi Miyauchi, Akiko Takeda, Akira Tanaka:
A Projected Gradient Method for Opinion Optimization with Limited Changes of Susceptibility to Persuasion. CIKM 2021: 1274-1283 - [c5]Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda:
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm. NeurIPS 2021: 25812-25823 - [i3]Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda:
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm. CoRR abs/2102.09191 (2021) - [i2]Naoki Marumo, Atsushi Miyauchi, Akiko Takeda, Akira Tanaka:
A Projected Gradient Method for Opinion Optimization with Limited Changes of Susceptibility to Persuasion. CoRR abs/2108.09865 (2021) - 2020
- [c4]Tomoharu Iwata, Naoki Marumo:
Co-Occurrence Estimation from Aggregated Data with Auxiliary Information. AAAI 2020: 4247-4254
2010 – 2019
- 2019
- [i1]Shinsaku Sakaue, Naoki Marumo:
Best-first Search Algorithm for Non-convex Sparse Minimization. CoRR abs/1910.01296 (2019) - 2018
- [j1]Takanori Maehara, Naoki Marumo, Kazuo Murota:
Continuous relaxation for discrete DC programming. Math. Program. 169(1): 199-219 (2018) - 2017
- [c3]Yasuhiro Fujiwara, Naoki Marumo, Mathieu Blondel, Koh Takeuchi, Hideaki Kim, Tomoharu Iwata, Naonori Ueda:
SVD-Based Screening for the Graphical Lasso. IJCAI 2017: 1682-1688 - [c2]Yasuhiro Fujiwara, Naoki Marumo, Mathieu Blondel, Koh Takeuchi, Hideaki Kim, Tomoharu Iwata, Naonori Ueda:
Scaling Locally Linear Embedding. SIGMOD Conference 2017: 1479-1492 - 2015
- [c1]Takanori Maehara, Naoki Marumo, Kazuo Murota:
Continuous Relaxation for Discrete DC Programming. MCO (1) 2015: 181-190
Coauthor Index
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