journal-article

A Generalized Time Rescaling Theorem for Temporal Point Processes
Temporal point processes are essential for modeling event dynamics in fields such as neuroscience and social media. The time rescaling …
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Combining global precipitation data and machine learning to predict flood peaks in ungauged areas with similar climate
Increasing flood risk due to urbanization and climate change poses a significant challenge to societies at global scale. Hydrologic …
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A multi-firearm, multi-orientation audio dataset of gunshots
This work describes a multi-firearm, multi-orientation, time-synchronized audio dataset collected in a semi-controlled real-world setting, which is ideal for gunshots detection and discharging firearm recognition tasks.
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Advancing flood warning procedures in ungauged basins with machine learning
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.
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Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning
We show a Talagrand-type concentration inequality for Multi-Task Learning (MTL), with which we establish sharp excess risk bounds for …
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Pareto-Optimal Model Selection via SPRINT-Race
In machine learning, the notion of multi-objective model selection (MOMS) refers to the problem of identifying the set of …
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