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Found 6 papers, 2 papers with code
Continual Learning with Weight Interpolation
Continual learning poses a fundamental challenge for modern machine learning systems, requiring models to adapt to new tasks while retaining knowledge from previous ones.
A Natural Gas Consumption Forecasting System for Continual Learning Scenarios based on Hoeffding Trees with Change Point Detection Mechanism
Forecasting natural gas consumption, considering seasonality and trends, is crucial in planning its supply and consumption and optimizing the cost of obtaining it, mainly by industrial entities.
Combining Self-labeling with Selective Sampling
We propose a new method that builds an ensemble classifier.
Lifelong Learning Natural Language Processing Approach for Multilingual Data Classification
The abundance of information in digital media, which in today's world is the main source of knowledge about current events for the masses, makes it possible to spread disinformation on a larger scale than ever before.
Increasing Depth of Neural Networks for Life-long Learning
Purpose: We propose a novel method for continual learning based on the increasing depth of neural networks.
Employing chunk size adaptation to overcome concept drift
Additionally, the possibility of concept drift appearance causes that the used algorithms must be ready for the continuous adaptation of the model to the changing data distributions.
