Прати
SUZUKI, Atsushi
SUZUKI, Atsushi
Assistant Professor, The University of Hong Kong
Верификована је имејл адреса на hku.hk - Почетна страница
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Навело
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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
132021
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
122021
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
112018
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
72019
Hyperbolic ordinal embedding
A Suzuki, J Wang, F Tian, A Nitanda, K Yamanishi
Asian Conference on Machine Learning, 1065-1080, 2019
62019
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
52016
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
42022
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
42021
Attributed subspace clustering
J Wang, L Xu, F Tian, A Suzuki, C Zhang, K Yamanishi
The 28th International Joint Conference on Artificial Intelligence, 3719-3725, 2019
32019
Hallucinations are inevitable but statistically negligible
A Suzuki, Y He, F Tian, Z Wang
arXiv preprint arXiv:2502.12187, 2025
2025
Foundation of Calculating Normalized Maximum Likelihood for Continuous Probability Models
A Suzuki, K Fukuzawa, K Yamanishi
arXiv preprint arXiv:2409.08387, 2024
2024
Tight and fast generalization error bound of graph embedding in metric space
A Suzuki, A Nitanda, T Suzuki, J Wang, F Tian, K Yamanishi
The 40th International Conference on Machine Learning 202, 33268--33284, 2023
2023
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