| 研究実績の概要 |
The main motivation behind my work was to design new machine learning methodologies built upon optimal transport theory. The main obstacle to this goal was computational, since optimal transport is notoriously costly to compute. To avoid that issue, I proposed 3 years ago a very efficient numerical scheme to solve optimal transport problems that can scale up to large scales and use recent progresses in hardware, namely GPGPUs. This breakthrough has inspired several works in the span of 3 years, in machine learning and beyond. Many of these breakthroughs were the direct fruit of this Wakate A funding. This funding resulted in publications published in the best research forums: 2 NIPS papers, 2 SIGGRAPH papers, 2 ICML papers, 2 SIAM journal papers, the organization of a NIPS workshop, several visits and collaborations.
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