Results 21 to 30 of about 28,537 (309)

Continuous-Action Q-Learning [PDF]

Machine Learning, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
del R. Millán, José, Posenato, Daniele, Dedieu, Eric   +2 more
openaire   +1 more source

Decentralized Federated Continual Learning Method Combined with Meta-learning [PDF]

Jisuanji kexue
For the problems of continual learning and data security in federated continual scenarios,a decentralized federated continual learning framework combined with meta-learning is constructed.First,in order to solve the problem of catastrophic forgetting in ...
HUANG Nan, LI Dongdong, YAO Jia, WANG Zhe
doaj   +1 more source

Subspace distillation for continual learning

Neural Networks, 2023
An ultimate objective in continual learning is to preserve knowledge learned in preceding tasks while learning new tasks. To mitigate forgetting prior knowledge, we propose a novel knowledge distillation technique that takes into the account the manifold structure of the latent/output space of a neural network in learning novel tasks.
Kaushik Roy, Christian Simon, Peyman Moghadam, Mehrtash Harandi   +3 more
openaire   +4 more sources

Variational Continual Learning

, 2017
Published at International Conference on Learning Representations (ICLR ...
Turner, RE, Bui, Thang, Li, Yingzhen, Cuong, Nguyen   +3 more
openaire   +2 more sources

Unsupervised Learning to Overcome Catastrophic Forgetting in Neural Networks

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2019
Continual learning is the ability to acquire a new task or knowledge without losing any previously collected information. Achieving continual learning in artificial intelligence (AI) is currently prevented by catastrophic forgetting, where training of a ...
Irene Munoz-Martin, Stefano Bianchi, Giacomo Pedretti, Octavian Melnic, Stefano Ambrogio, Daniele Ielmini   +5 more
doaj   +1 more source

Wheat Disease Classification Using Continual Learning

IEEE Access, 2023
As wheat is one of the major crops worldwide, therefore, accurate disease detection in wheat plants is critical for mitigating effects and halting disease spread. Nowadays, the detection of diseases through images using machine learning and deep learning
Abdulaziz Alharbi, Muhammad Usman Ghani Khan, Bushra Tayyaba   +2 more
doaj   +1 more source

Learning to Continually Learn

, 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 ...
Beaulieu, Shawn, Frati, Lapo, Miconi, Thomas, Lehman, Joel, Stanley, Kenneth O., Clune, Jeff, Cheney, Nick   +6 more
openaire   +2 more sources

Adversary Aware Continual Learning

IEEE Access
Continual learning approaches are useful to help a model learn new information or new tasks sequentially, while also retaining the previously acquired information.
Muhammad Umer, Robi Polikar
doaj   +1 more source

Bookworm continual learning: beyond zero-shot learning and continual learning

, 2020
Accepted by TASK-CV workshop at ECCV ...
Wang, Kai, Herranz, Luis, Dutta, Anjan, van de Weijer, Joost   +3 more
openaire   +2 more sources

Self-Net: Lifelong Learning via Continual Self-Modeling

Frontiers in Artificial Intelligence, 2020
Learning a set of tasks over time, also known as continual learning (CL), is one of the most challenging problems in artificial intelligence. While recent approaches achieve some degree of CL in deep neural networks, they either (1) store a new network ...
Jaya Krishna Mandivarapu, Blake Camp, Rolando Estrada   +2 more
doaj   +1 more source