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Shohei Hido
Shohei Hido
Preferred Networks, Inc.
Email verificata su preferred.jp - Home page
Titolo
Citata da
Citata da
Anno
Chainer: a next-generation open source framework for deep learning
S Tokui, K Oono, S Hido, J Clayton
Proceedings of workshop on machine learning systems (LearningSys) in the …, 2015
10512015
A least-squares approach to direct importance estimation
T Kanamori, S Hido, M Sugiyama
The Journal of Machine Learning Research 10, 1391-1445, 2009
5212009
Roughly balanced bagging for imbalanced data
S Hido, H Kashima, Y Takahashi
Statistical Analysis and Data Mining: The ASA Data Science Journal 2 (5‐6 …, 2009
2822009
Statistical outlier detection using direct density ratio estimation
S Hido, Y Tsuboi, H Kashima, M Sugiyama, T Kanamori
Knowledge and information systems 26, 309-336, 2011
2202011
Cupy: A numpy-compatible library for nvidia gpu calculations
R Okuta, Y Unno, D Nishino, S Hido, C Loomis
Proceedings of workshop on machine learning systems (LearningSys) in the …, 2017
2002017
Direct density ratio estimation for large-scale covariate shift adaptation
Y Tsuboi, H Kashima, S Hido, S Bickel, M Sugiyama
Journal of Information Processing 17, 138-155, 2009
1502009
A linear-time graph kernel
S Hido, H Kashima
2009 Ninth IEEE International Conference on Data Mining, 179-188, 2009
1422009
Time series data adaptation and sensor fusion systems, methods, and apparatus
JB Clayton, D Okanohara, S Hido
US Patent 10,410,113, 2019
1292019
Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection
T Kanamori, S Hido, M Sugiyama
Advances in neural information processing systems 21, 2008
982008
Unsupervised change analysis using supervised learning
S Hido, T Idé, H Kashima, H Kubo, H Matsuzawa
Advances in Knowledge Discovery and Data Mining: 12th Pacific-Asia …, 2008
862008
Inlier-based outlier detection via direct density ratio estimation
S Hido, Y Tsuboi, H Kashima, M Sugiyama, T Kanamori
2008 Eighth IEEE international conference on data mining, 223-232, 2008
832008
Machine learning heterogeneous edge device, method, and system
D Okanohara, JB Clayton, T Nishikawa, S Hido, N Kubota, N Ota, S Tokui
US Patent 9,990,587, 2018
562018
A density-ratio framework for statistical data processing
M Sugiyama, T Kanamori, T Suzuki, S Hido, J Sese, I Takeuchi, L Wang
IPSJ Transactions on Computer Vision and Applications 1, 183-208, 2009
512009
AMIOT: induced ordered tree mining in tree-structured databases
S Hido, H Kawano
Fifth IEEE International Conference on Data Mining (ICDM'05), 8 pp., 2005
502005
Jubatus: An open source platform for distributed online machine learning
S Hido, S Tokui, S Oda
NIPS 2013 Workshop on Big Learning, Lake Tahoe, 2013
422013
Machine learning with model filtering and model mixing for edge devices in a heterogeneous environment
D Okanohara, JB Clayton, T Nishikawa, S Hido, N Kubota, N Ota, S Tokui
US Patent 10,387,794, 2019
402019
Technique for classifying data
S Hido
US Patent 9,218,572, 2015
312015
System for inspecting information processing unit to which software update is applied
S Hido, S Munetoh, S Suzuki, N Uramoto, S Yoshihama
US Patent 8,887,146, 2014
242014
Modeling patent quality: A system for large-scale patentability analysis using text mining
S Hido, S Suzuki, R Nishiyama, T Imamichi, R Takahashi, T Nasukawa, ...
Information and Media Technologies 7 (3), 1180-1191, 2012
242012
Increasing Availability of an Industrial Control System
K Hamzaoui, S Hido, S Suzuki, S Yoshihama
US Patent App. 13/365,626, 2012
232012
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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