Motonobu Kanagawa
TitelCiteras avÅr
Gaussian processes and kernel methods: A review on connections and equivalences
M Kanagawa, P Hennig, D Sejdinovic, BK Sriperumbudur
arXiv preprint arXiv:1807.02582, 2018
282018
Convergence guarantees for kernel-based quadrature rules in misspecified settings
M Kanagawa, BK Sriperumbudur, K Fukumizu
Advances in Neural Information Processing Systems, 3288-3296, 2016
272016
Convergence analysis of deterministic kernel-based quadrature rules in misspecified settings
M Kanagawa, BK Sriperumbudur, K Fukumizu
Foundations of Computational Mathematics, 1-40, 2019
172019
Filtering with state-observation examples via kernel monte carlo filter
M Kanagawa, Y Nishiyama, A Gretton, K Fukumizu
Neural computation 28 (2), 382-444, 2016
132016
Monte Carlo filtering using kernel embedding of distributions
M Kanagawa, Y Nishiyama, A Gretton, K Fukumizu
Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
102014
Large sample analysis of the median heuristic
D Garreau, W Jitkrittum, M Kanagawa
arXiv preprint arXiv:1707.07269, 2017
82017
Unsupervised group matching with application to cross-lingual topic matching without alignment information
T Iwata, M Kanagawa, T Hirao, K Fukumizu
Data mining and knowledge discovery 31 (2), 350-370, 2017
42017
Kernel recursive abc: Point estimation with intractable likelihood
T Kajihara, M Kanagawa, K Yamazaki, K Fukumizu
arXiv preprint arXiv:1802.08404, 2018
32018
Model-based kernel sum rule: kernel Bayesian inference with probabilistic models
Y Nishiyama, M Kanagawa, A Gretton, K Fukumizu
Machine Learning, 1-34, 2020
12020
On the positivity and magnitudes of Bayesian quadrature weights
T Karvonen, M Kanagawa, S Särkkä
Statistics and Computing 29 (6), 1317-1333, 2019
12019
Convergence Guarantees for Adaptive Bayesian Quadrature Methods
M Kanagawa, P Hennig
Advances in Neural Information Processing Systems, 6234-6245, 2019
12019
Model Selection for Simulator-based Statistical Models: A Kernel Approach
T Kajihara, M Kanagawa, Y Nakaguchi, K Khandelwal, K Fukumiziu
arXiv preprint arXiv:1902.02517, 2019
2019
Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference
K Muandet, M Kanagawa, S Saengkyongam, S Marukatat
arXiv preprint arXiv:1805.08845, 2018
2018
Empirical representations of probability distributions via kernel mean embeddings
M Kanagawa
2016
Counterfactual Mean Embedding
K Muandet, M Kanagawa, S Saengkyongam, S Marukatat
a∈ A 1, 1, 0
Supplementary materials for “Convergence guarantees for kernel-based quadrature rules in misspecified settings”
M Kanagawa, BK Sriperumbudur, K Fukumizu
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Artiklar 1–16