PBES: PCA Based Exemplar Sampling Algorithm for Continual Learning

• URL: http://arxiv.org/abs/2312.09352v1
• Date: Thu, 14 Dec 2023 21:27:38 GMT
• Title: PBES: PCA Based Exemplar Sampling Algorithm for Continual Learning
• Authors: Sahil Nokhwal and Nirman Kumar
• Abstract summary: We propose a novel exemplar selection approach based on Principal Component Analysis (PCA) and median sampling, and a neural network training regime in the setting of class-incremental learning. This approach avoids the pitfalls due to outliers in the data and is both simple to implement and use across various incremental machine learning models.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a novel exemplar selection approach based on Principal Component Analysis (PCA) and median sampling, and a neural network training regime in the setting of class-incremental learning. This approach avoids the pitfalls due to outliers in the data and is both simple to implement and use across various incremental machine learning models. It also has independent usage as a sampling algorithm. We achieve better performance compared to state-of-the-art methods.

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