• Source: Scopus
  • Calculated based on no. of publications stored in Pure and citations from Scopus
20012016

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Dive into the research topics where Kei Kobayashi is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
  • 1 Similar Profiles
  • Flattening the density gradient for eliminating spatial centrality to reduce hubness

    Hara, K., Suzuki, I., Kobayashi, K., Fukumizu, K. & Radovanovíc, M., 2016, 30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press, p. 1659-1665 7 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)
  • Localized centering: Reducing hubness in large-sample data

    Hara, K., Suzuki, I., Shimbo, M., Kobayashi, K., Fukumizu, K. & Radovanovic, M., 2015 Jun 1, Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015. AI Access Foundation, Vol. 4. p. 2645-2651 7 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    15 Citations (Scopus)
  • Reducing hubness: A cause of vulnerability in recommender systems

    Hara, K., Suzuki, I., Kobayashi, K. & Fukumizu, K., 2015 Aug 9, SIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, Inc, p. 815-818 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)
  • Reducing hubness for kernel regression

    Hara, K., Suzuki, I., Kobayashi, K., Fukumizu, K. & Radovanović, M., 2015, Similarity Search and Applications - 8th International Conference, SISAP 2015, Proceedings. Connor, R., Amato, G., Falchi, F. & Gennaro, C. (eds.). Springer Verlag, p. 339-344 6 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9371).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Statistical analysis via the curvature of data space

    Kobayashi, K., Mitsuru, O. & Wynn, H. P., 2015, Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2014. Mohammad-Djafari, A., Barbaresco, F. & Barbaresco, F. (eds.). American Institute of Physics Inc., p. 97-104 8 p. (AIP Conference Proceedings; vol. 1641).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution