摘要
由一名新闻记者兼机器人与机器学习的新闻编辑每日新闻-调查人员发布了关于马学习的新报告。根据NewsRx记者在《中国人民日报》上的新闻报道，研究表明：“准确预测观测时间序列的未来演变是当前数据驱动研究的首要挑战。虽然现有技术难以从时间相关性中获得有用的表征，但时空域的高维数一直被认为是障碍。”导致了维度诅咒和过度资源消耗。本研究的资助单位包括国家自然科学基金、上海市科学技术委员会。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting originating in Shanghai, People’s Re public of China, by NewsRx journalists, research stated, “Accurate prediction of the future evolution of observational time series is a paramount challenge in c urrent datadriven research. While existing techniques struggle to learn useful representations from the temporal correlations, the high dimensionality in spati al domain is always considered as obstacle, leading to the curse of dimensionali ty and excessive resource consumption.” Financial supporters for this research include National Natural Science Foundati on of China, Science and Technology Commission of Shanghai Municipality.
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