Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction

WWW '19: The Web Conference on The World Wide Web Conference WWW 2019, pp. 2181-2191, 2019.

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Abstract:

Spatial-temporal prediction is a fundamental problem for constructing smart city, which is useful for tasks such as traffic control, taxi dispatching, and environment policy making. Due to data collection mechanism, it is common to see data collection with unbalanced spatial distributions. For example, some cities may release taxi data fo...More

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