E-LIB Suche - Ergebnisse für: Sugiyama, Mahito

1

Bringing Structure to Naturalness: On the Naturalness of AS..:

, In: Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings,

Pârțachi, Profir-Petru ; Sugiyama, Mahito - p. 378-379 , 2024

Link: https://dl.acm.org/doi/1..

2

How graph features from message passing affect graph classi..:

Yamada, Masatsugu ; Sugiyama, Mahito
Intelligent Data Analysis. 28 (2024) 1 - p. 57-75 , 2024

Link: https://doi.org/10.3233/..

3

Bringing Structure to Naturalness: On the Naturalness of AS..:

, In: 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion),

Partachi, Profir-Petru ; Sugiyama, Mahito - p. 378-379 , 2024

Link: https://doi.org/10.1145/..

4

Artificial neural network encoding of molecular wavefunctio..:

Hagai, Masaya ; Sugiyama, Mahito ; Tsuda, Koji.
Digital Discovery. 2 (2023) 3 - p. 634-650 , 2023

Link: https://doi.org/10.1039/..

5

Unsupervised Tensor Based Feature Extraction From Multivari..:

Matsue, Kiyotaka ; Sugiyama, Mahito
IEEE Access. 11 (2023) - p. 116277-116295 , 2023

Link: https://doi.org/10.1109/..

6

Molecular Graph Generation by Decomposition and Reassemblin:

Yamada, Masatsugu ; Sugiyama, Mahito
ACS Omega. 8 (2023) 22 - p. 19575-19586 , 2023

Link: https://doi.org/10.1021/..

7

Non-negative low-rank approximations for multi-dimensional ..:

Ghalamkari, Kazu ; Sugiyama, Mahito
Information Geometry. 6 (2023) 1 - p. 257-292 , 2023

Link: https://doi.org/10.1007/..

8

Unsupervised feature extraction from multivariate time seri..:

Matsue, Kiyotaka ; Sugiyama, Mahito
Intelligent Data Analysis. 26 (2022) 6 - p. 1451-1467 , 2022

Link: https://doi.org/10.3233/..

9

Investigating Overparameterization for Non-Negative Matrix ..:

, In: Proceedings of the 15th ACM Conference on Recommender Systems,

Kawakami, Yuhi ; Sugiyama, Mahito - p. 685-690 , 2021

Link: https://dl.acm.org/doi/1..

10

Testing machine learning code using polyhedral region:

, In: Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering,

Ahmed, Md Sohel ; Ishikawa, Fuyuki ; Sugiyama, Mahito - p. 1533-1536 , 2020

Link: https://dl.acm.org/doi/1..

11

Artificial Neural Networks Applied as Molecular Wave Functi..:

Yang, Peng-Jian ; Sugiyama, Mahito ; Tsuda, Koji.
Journal of Chemical Theory and Computation. 16 (2020) 6 - p. 3513-3529 , 2020

Link: https://doi.org/10.1021/..

12

Coordinate Descent Method for Log-linear Model on Posets:

, In: 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA),

Hayashi, Shota ; Sugiyama, Mahito ; Matsushima, Shin - p. 99-108 , 2020

Link: https://doi.org/10.1109/..

13

Legendre decomposition for tensors*:

Sugiyama, Mahito ; Nakahara, Hiroyuki ; Tsuda, Koji
Journal of Statistical Mechanics: Theory and Experiment. 2019 (2019) 12 - p. 124017 , 2019

Link: https://doi.org/10.1088/..

14

Detecting Anomalous Energy Consumption from Profiles:

Abe, Hiroto ; Bogaki, Kazuaki ; Rijal, H.B..
IOP Conference Series: Earth and Environmental Science. 294 (2019) 1 - p. 012072 , 2019

Link: https://doi.org/10.1088/..

15

graphkernels: R and Python packages for graph comparison:

Sugiyama, Mahito ; Ghisu, M Elisabetta ; Llinares-López, Felipe..
Bioinformatics. 34 (2017) 3 - p. 530-532 , 2017

Link: https://doi.org/10.1093/..