Advances and challenges in meta-learning: A technical review
A Vettoruzzo, MR Bouguelia… - … on Pattern Analysis …, 2024 - ieeexplore.ieee.org
Meta-learning empowers learning systems with the ability to acquire knowledge from
multiple tasks, enabling faster adaptation and generalization to new tasks. This review …
multiple tasks, enabling faster adaptation and generalization to new tasks. This review …
Meta-learning with task-adaptive loss function for few-shot learning
In few-shot learning scenarios, the challenge is to generalize and perform well on new
unseen examples when only very few labeled examples are available for each task. Model …
unseen examples when only very few labeled examples are available for each task. Model …
Simpleshot: Revisiting nearest-neighbor classification for few-shot learning
Few-shot learners aim to recognize new object classes based on a small number of labeled
training examples. To prevent overfitting, state-of-the-art few-shot learners use meta …
training examples. To prevent overfitting, state-of-the-art few-shot learners use meta …
Finding task-relevant features for few-shot learning by category traversal
Few-shot learning is an important area of research. Conceptually, humans are readily able
to understand new concepts given just a few examples, while in more pragmatic terms …
to understand new concepts given just a few examples, while in more pragmatic terms …
Laplacian regularized few-shot learning
We propose a transductive Laplacian-regularized inference for few-shot tasks. Given any
feature embedding learned from the base classes, we minimize a quadratic binary …
feature embedding learned from the base classes, we minimize a quadratic binary …
Diagnostic value and prognostic significance of nucleated red blood cells (NRBCs) in selected medical conditions
K Pikora, A Krętowska-Grunwald, M Krawczuk-Rybak… - Cells, 2023 - mdpi.com
Nucleated red blood cells (NRBCs) are premature erythrocyte precursors that reside in the
bone marrow of humans of all ages as an element of erythropoiesis. They rarely present in …
bone marrow of humans of all ages as an element of erythropoiesis. They rarely present in …
Hyperbolic image embeddings
V Khrulkov, L Mirvakhabova… - Proceedings of the …, 2020 - openaccess.thecvf.com
Computer vision tasks such as image classification, image retrieval, and few-shot learning
are currently dominated by Euclidean and spherical embeddings so that the final decisions …
are currently dominated by Euclidean and spherical embeddings so that the final decisions …
Boosting few-shot learning with adaptive margin loss
Few-shot learning (FSL) has attracted increasing attention in recent years but remains
challenging, due to the intrinsic difficulty in learning to generalize from a few examples. This …
challenging, due to the intrinsic difficulty in learning to generalize from a few examples. This …
Adaptive cross-modal few-shot learning
Metric-based meta-learning techniques have successfully been applied to few-shot
classification problems. In this paper, we propose to leverage cross-modal information to …
classification problems. In this paper, we propose to leverage cross-modal information to …
Meta-learning with adaptive hyperparameters
Despite its popularity, several recent works question the effectiveness of MAML when test
tasks are different from training tasks, thus suggesting various task-conditioned methodology …
tasks are different from training tasks, thus suggesting various task-conditioned methodology …