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Cold Start Active Learning Strategies in the Context of Imbalanced Classification
We present novel active learning strategies dedicated to providing a solution to the cold start stage, i. e. initializing the classification of a large set of data with no attached labels.
Computing flood probabilities using Twitter: application to the Houston urban area during Harvey
In this paper, we investigate the conversion of a Twitter corpus into geo-referenced raster cells holding the probability of the associated geographical areas of being flooded.
Extracting localized information from a Twitter corpus for flood prevention
In this paper, we discuss the collection of a corpus associated to tropical storm Harvey, as well as its analysis from both spatial and topical perspectives.
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