2007
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Takuya Furukawa Forestry and Forest Products Research Institute Verified email at affrc.go.jp. Hannah Windley Australian National University Verified email at anu.edu.au. ... JJ Sato, T Shimada, D Kyogoku, T Komura, S Uemura, T Saitoh, Y Isagi. Journal of Mammalogy 99 (4), 952-964, 2018. 42:
The Science of Nature. 2023-12 | Journal article. DOI: 10.1007/s00114-023-01881-6. Contributors : Takuya Shimada; Kimiko Okabe; Shun’ichi Makino; Shoko Nakamura; Saori Fujii. Show more detail. Source : check_circle. Crossref. Resource allocation strategies in the reproductive organs of Fagaceae species. Ecological Research.
Takuya Shimada1, Han Bao1,2, Issei Sato1,2, and Masashi Sugiyama2,1. 1The University of Tokyo. 2RIKEN. Abstract. Pairwise similarities and dissimilarities between data points might be easier to obtain than fully labeled data in real-world classification problems, e.g., in privacy-aware situations.
Takuya Shimada • European University Institute. Researcher. Department of History. Research projects, clusters and working groups. Completed. Decentering Eurocentrism. Thesis title. The Tensho Embassy in Italy (1585): Sixteenth-century Italian understandings of Japan and Japanese culture. Supervisor. Giancarlo Casale. 2nd reader. Lucy Riall.
13 de abr. de 2021 · April 13 2021. Classification From Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization. In Special Collection: CogNet. Takuya Shimada, Han Bao, Issei Sato, Masashi Sugiyama. Author and Article Information. Neural Computation (2021) 33 (5): 1234–1268. https://doi.org/10.1162/neco_a_01373. Article history. Cite.
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20 de jun. de 2019 · Takuya Shimada, Shoichiro Yamaguchi, Kohei Hayashi, Sosuke Kobayashi. Data augmentation by mixing samples, such as Mixup, has widely been used typically for classification tasks. However, this strategy is not always effective due to the gap between augmented samples for training and original samples for testing.
