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Found 4 papers, 1 papers with code
Predicting Seriousness of Injury in a Traffic Accident: A New Imbalanced Dataset and Benchmark
The paper introduces a new dataset to assess the performance of machine learning algorithms in the prediction of the seriousness of injury in a traffic accident.
Deep Incremental Boosting
This paper introduces Deep Incremental Boosting, a new technique derived from AdaBoost, specifically adapted to work with Deep Learning methods, that reduces the required training time and improves generalisation.
Adapting Resilient Propagation for Deep Learning
The Resilient Propagation (Rprop) algorithm has been very popular for backpropagation training of multilayer feed-forward neural networks in various applications.
Transfer learning approach for financial applications
Artificial neural networks learn how to solve new problems through a computationally intense and time consuming process.
