Results 11 to 20 of about 6,336,923 (296)
Variational Continual Learning [PDF]
CoRR, 2017 Published at International Conference on Learning Representations (ICLR ...
Turner, RE +3 more
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Continual learning for efficient machine learning [PDF]
, 2020 Deep learning has enjoyed tremendous success over the last decade, but the training of practically useful deep models remains highly inefficient both in terms of the number of weight updates and training samples. To address one aspect of these issues, this thesis studies the continual learning setting whereby a model utilizes a sequence of tasks ...
Chaudhry, Arslan
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Learning to Prompt for Continual Learning
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 The mainstream paradigm behind continual learning has been to adapt the model parameters to non-stationary data distributions, where catastrophic forgetting is the central challenge. Typical methods rely on a rehearsal buffer or known task identity at test time to retrieve learned knowledge and address forgetting, while this work presents a new ...
Zifeng Wang 0002 +9 more
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Applied Sciences, 2023 This paper proposes a supervised classification algorithm capable of continual learning by utilizing an Adaptive Resonance Theory (ART)-based growing self-organizing clustering algorithm.
Naoki Masuyama +3 more
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Learning continuous models for continuous physics
Communications Physics, 2023 AbstractDynamical systems that evolve continuously over time are ubiquitous throughout science and engineering. Machine learning (ML) provides data-driven approaches to model and predict the dynamics of such systems. A core issue with this approach is that ML models are typically trained on discrete data, using ML methodologies that are not aware of ...
Aditi S. Krishnapriyan +3 more
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Bilevel Continual Learning [PDF]
2021 International Joint Conference on Neural Networks (IJCNN), 2021 Continual learning (CL) studies the problem of learning a sequence of tasks, one at a time, such that the learning of each new task does not lead to the deterioration in performance on the previously seen ones while exploiting previously learned features.
Ammar Shaker +3 more
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Continual Learning in Practice [PDF]
CoRR, 2019 Presented at the NeurIPS 2018 workshop on Continual Learning https://sites.google.com/view/continual2018 ...
Tom Diethe +4 more
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Bookworm continual learning: beyond zero-shot learning and continual learning
CoRR, 2020 Accepted by TASK-CV workshop at ECCV ...
Kai Wang 0060 +3 more
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CLRS: Continual Learning Benchmark for Remote Sensing Image Scene Classification
Sensors, 2020 Remote sensing image scene classification has a high application value in the agricultural, military, as well as other fields. A large amount of remote sensing data is obtained every day. After learning the new batch data, scene classification algorithms
Haifeng Li +6 more
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Representational Continuity for Unsupervised Continual Learning
, 2021 Continual learning (CL) aims to learn a sequence of tasks without forgetting the previously acquired knowledge. However, recent CL advances are restricted to supervised continual learning (SCL) scenarios. Consequently, they are not scalable to real-world applications where the data distribution is often biased and unannotated. In this work, we focus on
Divyam Madaan +4 more
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