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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,181 papers · 148 categories

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0111 · Jun 201219922001200920182026
4 results for overgeneralization

The paper tackles overfitting in deep neural networks and proposes a consensus-based algorithm to avoid it.

problem Overfitting in deep neural networks.
method Separating correctly and incorrectly classified samples, analyzing dynamics during training, and proposing a consensus-based classification algorithm.
result The consensus-based algorithm significantly improves classification accuracy, especially with limited training samples.

In this paper we study output coding for multi-label prediction. For a multi-label output coding to be discriminative, it is important that codewords for different label vectors are significantly different from each other. In the meantime, unlike in traditional coding theory, codewords in output coding are to be predic…

2012-06-27abs ↗pdf ↗

Process mining is a research field focused on the analysis of event data with the aim of extracting insights in processes. Applying process mining techniques on data from smart home environments has the potential to provide valuable insights in (un)healthy habits and to contribute to ambient assisted living solutions. …

2016-09-12abs ↗pdf ↗

The paper proposes a consensus algorithm to improve deep neural network interpretability and accuracy in mortality prediction.

problem The black-box nature and overgeneralization of deep neural networks in healthcare applications.
method An (nn, kk) consensus algorithm that is insensitive to adversarial examples and can reliably reject out-of-distribution samples.
result The consensus algorithm improves both prediction accuracy and interpretability of deep neural network models in mortality prediction.