摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-研究人员详细介绍机器学习的新数据。根据来自…的消息宾夕法尼亚州匹兹堡，由NewsR X记者报道，研究称，"我们引入了一种函数空间上随机映射分布的正则化最优传输问题函数域之间可以用（无限维）希尔伯特-施密特近似算子将函数的Hilbert空间映射到其他空间。对于许多机器学习应用，从函数空间中抽取的s样本可以自然地查看数据，例如曲线和曲面高D值"。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Machine Learning. According to news originating fromPittsburgh, Pennsylvania, by NewsR x correspondents, research stated, “We introduce a formulation ofregularized op timal transport problem for distributions on function spaces, where the stochast ic mapbetween functional domains can be approximated in terms of an (infinite-d imensional) Hilbert-Schmidtoperator mapping a Hilbert space of functions to ano ther. For numerous machine learning applications,data can be naturally viewed a s samples drawn from spaces of functions, such as curves and surfaces, inhigh d imensions.”
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