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SUZUKI, Atsushi
SUZUKI, Atsushi
Assistant Professor (UK Lecturer), King's College London
Verified email at kcl.ac.uk - Homepage
Title
Cited by
Cited by
Year
Generalization bounds for graph embedding using negative sampling: Linear vs hyperbolic
A Suzuki, A Nitanda, L Xu, K Yamanishi, M Cavazza
Advances in Neural Information Processing Systems 34, 1243-1255, 2021
102021
Generalization error bound for hyperbolic ordinal embedding
A Suzuki, A Nitanda, J Wang, L Xu, K Yamanishi, M Cavazza
International Conference on Machine Learning, 10011-10021, 2021
102021
Exact calculation of normalized maximum likelihood code length using Fourier analysis
A Suzuki, K Yamanishi
2018 IEEE International Symposium on Information Theory (ISIT), 1211-1215, 2018
102018
Orderly subspace clustering
J Wang, A Suzuki, L Xu, F Tian, L Yang, K Yamanishi
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5264-5272, 2019
62019
Hyperbolic ordinal embedding
A Suzuki, J Wang, F Tian, A Nitanda, K Yamanishi
Asian Conference on Machine Learning, 1065-1080, 2019
52019
Structure selection for convolutive non-negative matrix factorization using normalized maximum likelihood coding
A Suzuki, K Miyaguchi, K Yamanishi
2016 IEEE 16th International Conference on Data Mining (ICDM), 1221-1226, 2016
42016
Attributed subspace clustering
J Wang, L Xu, F Tian, A Suzuki, C Zhang, K Yamanishi
32019
RGB Color Model Aware Computational Color Naming and Its Application to Data Augmentation
Z Yan, L Xu, A Suzuki, J Wang, J Cao, J Huang
2022 IEEE International Conference on Big Data (Big Data), 1172-1181, 2022
22022
Fourier-analysis-based form of normalized maximum likelihood: Exact formula and relation to complex bayesian prior
A Suzuki, K Yamanishi
IEEE Transactions on Information Theory 67 (9), 6164-6178, 2021
22021
Tight and fast generalization error bound of graph embedding in metric space
A Suzuki, A Nitanda, T Suzuki, J Wang, F Tian, K Yamanishi
arXiv preprint arXiv:2305.07971, 2023
2023
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