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Lecture 10.1: Fusion, co-learning, and new trend (Multimodal Machine Learning, CMU)

Lecture 10.1: Fusion, co-learning, and new trend (Multimodal Machine Learning, Carnegie Mellon University)

Topics: Multi-kernel learning and fusion; Few shot learning and co-learning

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Carnegie Mellon University 11-777 Multimodal Machine Learning, 2020 Fall
Website: https://cmu-multicomp-lab.github.io/mmml-course/fall2020/
Instructor: Louis-Philippe Morency

Multimodal machine learning (MMML) is a vibrant multi-disciplinary research field which studies computational approaches for modeling heterogenous data from multiple modalities. The course presents fundamental mathematical concepts in machine learning and deep learning relevant to the five main challenges in multimodal machine learning: (1) multimodal representation learning, (2) translation & mapping, (3) modality alignment, (4) multimodal fusion and (5) co-learning. The course also discusses recent state-of-the-art models and applications of multimodal machine learning.

Видео Lecture 10.1: Fusion, co-learning, and new trend (Multimodal Machine Learning, CMU) канала LP Morency
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8 ноября 2020 г. 19:14:31
01:12:37
Яндекс.Метрика