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ACM Multimedia 2023Tutorial Summaries

Efficient Multimedia Computing: Unleashing the Power of AutoML

Debanjan Datta, Gerald Friedland

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1145/3581783.3613858 ↗

摘要

As the field of multimedia computing has grown rapidly, so has the need for larger datasets[5] and increased modeling capacity. Navigating this complex landscape often necessitates the use of sophisticated tools and cloud architectures, which all need to be addressed before the actual research commences. Recently, AutoML, an innovation previously exclusive to tabular data, has expanded to encompass multimedia data. This development has the potential to greatly streamline the research process, allowing researchers to shift their focus from model construction to the core content of their problems. In doing so, AutoML not only optimizes resource utilization but also boosts the reproducibility of results. The aim of this tutorial is to acquaint the multimedia community with AutoML technologies, underscoring their advantages and their practical applications in the field.