Results 11 to 20 of about 11,171,980 (304)

Autoapprentissage Self-learning

Kufa Journal of Arts
In traditional pedagogy, the transmission of knowledge remains at the heart of the teaching profession. He gives lectures. He plays a central and dominant role while the learner plays only a secondary role. Although this method has all sorts of advantages, it does not create activity and independence in the learner.
Asmaa Kadhum
openaire   +3 more sources

Intelligent Control System for Brain-Controlled Mobile Robot Using Self-Learning Neuro-Fuzzy Approach [PDF]

Sensors
Brain-computer interface (BCI) provides direct communication and control between the human brain and physical devices. It is achieved by converting EEG signals into control commands.
Zahid Razzaq, Nihad Brahimi, Hafiz Zia Ur Rehman, Zeashan Hameed Khan   +3 more
doaj   +2 more sources

HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units [PDF]

IEEE/ACM Transactions on Audio Speech and Language Processing, 2021
Self-supervised approaches for speech representation learning are challenged by three unique problems: (1) there are multiple sound units in each input utterance, (2) there is no lexicon of input sound units during the pre-training phase, and (3) sound ...
Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, R. Salakhutdinov, Abdel-rahman Mohamed   +5 more
semanticscholar   +1 more source

Emerging Properties in Self-Supervised Vision Transformers [PDF]

IEEE International Conference on Computer Vision, 2021
In this paper, we question if self-supervised learning provides new properties to Vision Transformer (ViT) [16] that stand out compared to convolutional networks (convnets). Beyond the fact that adapting self-supervised methods to this architecture works
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, J. Mairal, Piotr Bojanowski, Armand Joulin   +6 more
semanticscholar   +1 more source

STEMM: Self-learning with Speech-text Manifold Mixup for Speech Translation [PDF]

Annual Meeting of the Association for Computational Linguistics, 2022
How to learn a better speech representation for end-to-end speech-to-text translation (ST) with limited labeled data? Existing techniques often attempt to transfer powerful machine translation (MT) capabilities to ST, but neglect the representation ...
Qingkai Fang, Rong Ye, Lei Li, Yang Feng, Mingxuan Wang   +4 more
semanticscholar   +1 more source

Self-Refine: Iterative Refinement with Self-Feedback [PDF]

Neural Information Processing Systems, 2023
Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self-Refine, an approach for improving initial outputs from LLMs through iterative ...
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, S. Welleck, Bodhisattwa Prasad Majumder, Shashank Gupta, A. Yazdanbakhsh, Peter Clark   +14 more
semanticscholar   +1 more source

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture [PDF]

Computer Vision and Pattern Recognition, 2023
This paper demonstrates an approach for learning highly semantic image representations without relying on hand-crafted data-augmentations. We introduce the Image-based Joint-Embedding Predictive Architecture (I-JEPA), a non-generative approach for self ...
Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas   +7 more
semanticscholar   +1 more source

Unsupervised domain adaptation for cross-modality liver segmentation via joint adversarial learning and self-learning [PDF]

Applied Soft Computing, 2021
Liver segmentation on images acquired using computed tomography (CT) and magnetic resonance imaging (MRI) plays an important role in clinical management of liver diseases.
Jin Hong, Simon Yu, Weitian Chen
semanticscholar   +1 more source

Self-learning Machines based on Hamiltonian Echo Backpropagation [PDF]

Physical Review X, 2021
A physical self-learning machine can be defined as a nonlinear dynamical system that can be trained on data (similar to artificial neural networks), but where the update of the internal degrees of freedom that serve as learnable parameters happens ...
V. López-Pastor, F. Marquardt
semanticscholar   +1 more source

DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction [PDF]

Neural Information Processing Systems, 2023
We study the problem of decomposing a complex text-to-sql task into smaller sub-tasks and how such a decomposition can significantly improve the performance of Large Language Models (LLMs) in the reasoning process.
M. Pourreza, Davood Rafiei
semanticscholar   +1 more source