Conference Proceedings

METEOR: Learning Memory and Time Efficient Representations from Multi-modal Data Streams

A Silva, S Karunasekera, C Leckie, L Luo

CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management | ACM | Published : 2020


Many learning tasks involve multi-modal data streams, where continuous data from different modes convey a comprehensive description about objects. A major challenge in this context is how to efficiently interpret multi-modal information in complex environments. This has motivated numerous studies on learning unsupervised representations from multi-modal data streams. These studies aim to understand higher-level contextual information (e.g., a Twitter message) by jointly learning embeddings for the lower-level semantic units in different modalities (e.g., text, user, and location of a Twitter message). However, these methods directly associate each low-level semantic unit with a continuous em..

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