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In this work we present a prototype ML-based framework for flood warning and flood peak prediction based on catchment characteristics and precipitation profiles. Based on this framework we analyze a host of findings across 18 distinct hydroclimatic regions across the contiguous US.

We show a Talagrand-type concentration inequality for Multi-Task Learning (MTL), with which we establish sharp excess risk bounds for …

In machine learning, the notion of multi-objective model selection (MOMS) refers to the problem of identifying the set of …