首页|Investigators from Department of Electronic Computer & Biomedical Engineering Report New Data on Machine Learning (Interpretability of Machine Learning: Recent Advances and Future Prospects)
Investigators from Department of Electronic Computer & Biomedical Engineering Report New Data on Machine Learning (Interpretability of Machine Learning: Recent Advances and Future Prospects)
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Research findings on Machine Learning are discussed in a new report. According to news reporting originating in Toronto, Canada, by NewsRx journalists, research stated, "The proliferation of machine learning (ML) has drawn unprecedented interest in the study of various multimedia contents such as text, image, audio, and video, among others. Consequently, understanding and learning MLbased representations have taken center stage in knowledge discovery in intelligent multimedia research and applications." The news reporters obtained a quote from the research from the Department of Electronic Computer & Biomedical Engineering, "Nevertheless, the black-box nature of contemporary ML, especially in deep neural networks, has posed a primary challenge for ML-based representation learning. To address this black-box problem, studies on the interpretability of ML have attracted tremendous interest in recent years. This article presents a survey on recent advances in and future prospects for the interpretability of ML, with several application examples pertinent to multimedia computing, including text-image cross-modal representation learning, face recognition, and the recognition of objects."
TorontoCanadaNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningDepartment of Electronic Computer & Biomedical Engineering
NETL
NSTL
IEEE
