Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Shohei Hido"'
Autor:
Rikiya Takahashi, Toshiya Watanabe, Akira Tajima, Rinju Yohda, Risa Nishiyama, Tsuyoshi Ide, Yusuke Kanehira, Shoko Suzuki, Takashi Imamichi, Takeshi Ueno, Shohei Hido, Tetsuya Nasukawa
Publikováno v:
Journal of Information Processing. 20:655-666
Current patent systems face a serious problem of declining quality of patents as the larger number of ap- plications make it difficult for patent officers to spend enough time for evaluating each application. For building a better patent system, it i
Publikováno v:
Knowledge and Information Systems. 26:309-336
We propose a new statistical approach to the problem of inlier-based outlier detection, i.e., finding outliers in the test set based on the training set consisting only of inliers. Our key idea is to use the ratio of training and test data densities
Publikováno v:
Statistical Analysis and Data Mining. 2:412-426
Publikováno v:
SDM
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common approach to compensating for the bias caused by covariate shift is to
Autor:
Masashi Sugiyama, Liwei Wang, Ichiro Takeuchi, Taiji Suzuki, Jun Sese, Takafumi Kanamori, Shohei Hido
Publikováno v:
IPSJ Transactions on Computer Vision and Applications. 1:183-208
In statistical pattern recognition, it is important to avoid density estimation since density estimation is often more difficult than pattern recognition itself. Following this idea—known as Vapnik’s principle, a statistical data processing frame
Autor:
Shohei Hido, Hiroyuki Kawano
Publikováno v:
Systems and Computers in Japan. 38:34-43
Publikováno v:
Journal of the Visualization Society of Japan. 24:463-466
Computational simulation became popular not only in the fields of physics or chemistry, but also medical, engineering, finance, and so on. Discovery of the best simulation parameters is an issue in order to fit the result of simulations to real exper
Publikováno v:
ICDM Workshops
Data values are uneven. Some data have higher (financial) values than others. Data with low value-density should be reduced in size or removed in order to make room for new data with higher values. Okanohara et al. [9] argued that the data values wil
Autor:
Shohei Hido, Michiaki Tatsubori
Publikováno v:
SRII Global Conference
False positives and negatives are inevitable in real-world classification problems. In general, machine-learning-based business process automation is still viable with reduced classification accuracy due to such false decisions, thanks to business mo
Autor:
Hisashi Kashima, Shohei Hido
Publikováno v:
ICDM
The design of a good kernel is fundamental for knowledge discovery from graph-structured data. Existing graph kernels exploit only limited information about the graph structures but are still computationally expensive. We propose a novel graph kernel