Meta-learning - Open Access .click

Results 41 to 50 of about 252,836 (257)

Online Meta-Learning

CoRR, 2019
ICML 2019. The first two authors contributed equally.
Chelsea Finn +3 more
openaire +3 more sources

Meta-Learning Symmetries by Reparameterization

CoRR, 2020
ICLR ...
Allan Zhou, Tom Knowles, Chelsea Finn
openaire +3 more sources

Multi-Stage Meta-Learning for Few-Shot with Lie Group Network Constraint

Entropy, 2020
Deep learning has achieved many successes in different fields but can sometimes encounter an overfitting problem when there are insufficient amounts of labeled samples.
Fang Dong, Li Liu, Fanzhang Li
doaj +1 more source

Robust Spike-Based Continual Meta-Learning Improved by Restricted Minimum Error Entropy Criterion

Entropy, 2022
The spiking neural network (SNN) is regarded as a promising candidate to deal with the great challenges presented by current machine learning techniques, including the high energy consumption induced by deep neural networks.
Shuangming Yang, Jiangtong Tan, Badong Chen +2 more
doaj +1 more source

Improving Domain-Generalized Few-Shot Text Classification with Multi-Level Distributional Signatures

Applied Sciences, 2023
Domain-generalized few-shot text classification (DG-FSTC) is a new setting for few-shot text classification (FSTC). In DG-FSTC, the model is meta-trained on a multi-domain dataset, and meta-tested on unseen datasets with different domains.
Xuyang Wang +8 more
doaj +1 more source

Few Shot Class Incremental Learning via Efficient Prototype Replay and Calibration

Entropy, 2023
Few shot class incremental learning (FSCIL) is an extremely challenging but valuable problem in real-world applications. When faced with novel few shot tasks in each incremental stage, it should take into account both catastrophic forgetting of old ...
Wei Zhang, Xiaodong Gu
doaj +1 more source

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

Molecular Oncology, EarlyView.
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source

Knowledge of Accredited Social Health Activists in India: a systematic review and meta analysis of evidence drawn from primary studies published between 2005 and 2022

BMC Health Services Research
Background Since the inception of the ASHAs in the year 2005, their work horizons have increased from Reproductive, Maternal, Newborn, Child, and Adolescent health (RMNCH + A), Communicable and Non-Communicable Diseases (CD & NCD) to oral health ...
Shambhavi Singh +7 more
doaj +1 more source

Sharing to Learn and Learning to Share; Fitting Together Meta, Multi-Task, and Transfer Learning: A Meta Review

IEEE Access
Integrating knowledge across different domains is an essential feature of human learning. Learning paradigms such as transfer learning, meta-learning, and multi-task learning reflect the human learning process by exploiting the prior knowledge for new ...
Richa Upadhyay +3 more
doaj +1 more source

Task-Adaptive Embedding Learning with Dynamic Kernel Fusion for Few-Shot Remote Sensing Scene Classification

Remote Sensing, 2021
The central goal of few-shot scene classification is to learn a model that can generalize well to a novel scene category (UNSEEN) from only one or a few labeled examples.
Pei Zhang +4 more
doaj +1 more source

few-shot learning
transfer learning
deep learning

machine learning