标杆管理
深度学习
计算机科学
水准点(测量)
人工智能
时间序列
机器学习
系列(地层学)
数据科学
古生物学
大地测量学
营销
业务
生物
地理
作者
Xinyuan Huang,Geoffrey Fox,Sergey Serebryakov,A. Krishna Mohan,Paweł Morkisz,Dipanwita Dutta
标识
DOI:10.1109/bigdata47090.2019.9005496
摘要
Deep learning for time series is an emerging area with close ties to industry, yet under represented in performance benchmarks for machine learning systems. In this paper, we present a landscape of deep learning applications applied to time series, and discuss the challenges and directions towards building a robust performance benchmark of deep learning workloads for time series data.
科研通智能强力驱动
Strongly Powered by AbleSci AI