Reproducibility and Experimental Design for Machine Learning on Audio and Multimedia Data

TitleReproducibility and Experimental Design for Machine Learning on Audio and Multimedia Data
Publication TypeConference Paper
Year of Publication2019
AuthorsFriedland, G.
Published inProceedings of the 27th ACM International Conference on Multimedia
Page(s)2709-2710
Date Published10/2019
PublisherACM
Abstract

This tutorial provides an actionable perspective on the experimental design for machine learning experiments on multimedia data. The tutorial consists of lectures and hands-on exercises. The lectures provide a theoretical introduction to machine learning design and signal processing. The thought framework presented is derived from the traditional experimental sciences which require published results to be self-contained with regards to reproducibility. In the practical exercises, we will work on calculating and measuring quantities like capacity or generalization ratio for different machine learners and data sets and discuss how these quantities relate to reproducible experimental design.

URLhttps://dl.acm.org/doi/abs/10.1145/3343031.3350545