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Crime hotspot forecasting is an important part of crime prevention and reducing the delay between a 911 call and the physical intervention. Current developments in the field focus on enriching the historical data and sophisticated point process analysis methods with a fixed grid. In the paper we present a simple spatio-temporal point process allowing one to perform exhaustive (literal) grid searches...
Photo identification is an important tool for estimating abundance and monitoring population trends over time. However, manually matching photographs to known individuals is time‐consuming. Motivated by recent developments in image recognition, we hosted a data science challenge on the crowdsourcing platform Kaggle to automate the identification of endangered North Atlantic right whales (Eubalaena...
This document describes an approach to the prob- lem of predicting dangerous seismic events in active coal mines up to 8 hours in advance. It was developed as a part of the AAIA'16 Data Mining Challenge: Predicting Dangerous Seismic Events in Active Coal Mines. The solutions presented consist of ensembles of various predictive models trained on different sets of features. The best one achieved a winning...
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