| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2014: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2013: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Outline of Final Research Achievements |
Our goal in this work was to provide a principled approach to carry out kernel/metric learning in an unsupervised way, to take advantage of large datasets of unlabeled data. We investigated this research avenue by focusing mostly on histogram data (bags-of-features). Using a combination of 3 known approaches by Aitchison, Lebanon and Hinton, we were able to propose different algorithms which perform at state-of-the art level or directly outperform competing approaches.
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