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Utilizing Priming to Identify Optimal Class Ordering to Alleviate Catastrophic Forgetting
While efforts are being made to quell catastrophic forgetting, there is a lack of research that looks into the importance of class ordering when training on new classes for incremental learning.
Incremental Deep Neural Network Learning using Classification Confidence Thresholding
This in turn leads to the concept of incremental learning where a model with its own architecture and initial trained set of data can identify unknown classes during the testing phase and autonomously update itself if evidence of a new class is detected.
Moving Towards Open Set Incremental Learning: Readily Discovering New Authors
This paper also develops a new metric that measures multiple attributes of clustering open set data.
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