Results 21 to 30 of about 6,336,923 (296)
Continual Barlow Twins: Continual Self-Supervised Learning for Remote Sensing Semantic Segmentation
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 In the field of earth observation (EO), continual learning (CL) algorithms have been proposed to deal with large datasets by decomposing them into several subsets and processing them incrementally.
Valerio Marsocci, Simone Scardapane
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, 2020 Continual lifelong learning requires an agent or model to learn many sequentially ordered tasks, building on previous knowledge without catastrophically forgetting it. Much work has gone towards preventing the default tendency of machine learning models to catastrophically forget, yet virtually all such work involves manually-designed solutions to the ...
Shawn Beaulieu +6 more
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Continual-Learning-of-Generative-Models-with-Limited-Data
, 2023 This repository contains the implementation of the paper ``Continual Learning of  Generative Models with Limited Data: From Wasserstein-1 Barycenter to Adaptive Coalescence.''
Mehmet Dedeoglu (14644163)
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Extending Gated Linear Networks for Continual Learning [PDF]
, 2022 openTo incrementally learn multiple tasks from an indefinitely long stream of data is a real challenge for traditional machine learning models. If not carefully controlled, the learning of new knowledge strongly impacts on a model’s learned abilities ...
MUNARI, MATTEO
core
Extensible Steganalysis via Continual Learning
Fractal and Fractional, 2022 To realize secure communication, steganography is usually implemented by embedding secret information into an image selected from a natural image dataset, in which the fractal images have occupied a considerable proportion.
Zhili Zhou +3 more
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Proceedings of the AAAI Conference on Artificial Intelligence, 2020 We propose a novel continual learning method called Residual Continual Learning (ResCL). Our method can prevent the catastrophic forgetting phenomenon in sequential learning of multiple tasks, without any source task information except the original network.
Janghyeon Lee 0001 +3 more
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CoRR, 2021 This paper introduces kernel continual learning, a simple but effective variant of continual learning that leverages the non-parametric nature of kernel methods to tackle catastrophic forgetting. We deploy an episodic memory unit that stores a subset of samples for each task to learn task-specific classifiers based on kernel ridge regression. This does
Derakhshani, M.M. +3 more
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Continual Learning through Hamilton Equations [PDF]
, 2022 Learning in a continual manner is one of the main challenges that the machine learning community is currently facing. The importance of the problem can be readily understood as soon as we consider settings where an agent is supposed to learn through an ...
Stefano Melacci +6 more
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Adversarial Continual Learning [PDF]
, 2020 Accepted at ECCV ...
Sayna Ebrahimi +4 more
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GMvandeVen/continual-learning: v1.0.0
, 2022 Version of the code used for the experiments in the article "Three types of incremental learning"
GMvandeVen
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