Robuta

https://www.amazon.science/publications/domain-aligned-clip-for-few-shot-classification Domain aligned CLIP for few-shot classification - Amazon Science Large vision-language representation learning models like CLIP have demonstrated impressive performance for zero-shot transfer to downstream tasks while... few shot classificationdomainalignedclipamazon https://deepai.org/publication/how-to-train-your-maml-to-excel-in-few-shot-classification How to Train Your MAML to Excel in Few-Shot Classification | DeepAI Jun 30, 2021 - 06/30/21 - Model-agnostic meta-learning (MAML) is arguably the most popular meta-learning algorithm nowadays, given its flexibility to incorp... how to trainfew shot classificationmaml https://deepai.org/publication/training-few-shot-classification-via-the-perspective-of-minibatch-and-pretraining Training few-shot classification via the perspective of minibatch and pretraining | DeepAI Apr 10, 2020 - 04/10/20 - Few-shot classification is a challenging task which aims to formulate the ability of humans to learn concepts from limited prior d... few shot classificationthe perspective https://openreview.net/forum?id=DiWRG9JTWZ MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation | OpenReview Out-of-distribution (OOD) problems in few-shot classification (FSC) occur when novel classes sampled from testing distributions differ from base classes drawn... few shot classificationspurious correlationnew https://www.mdpi.com/1424-8220/24/1/49 Few-Shot Classification with Meta-Learning for Urban Infrastructure Monitoring Using Distributed... This paper studies an advanced machine learning method, specifically few-shot classification with meta-learning, applied to distributed acoustic sensing (DAS)... few shot classificationmeta learning https://deepai.org/publication/adaptive-parametric-prototype-learning-for-cross-domain-few-shot-classification Adaptive Parametric Prototype Learning for Cross-Domain Few-Shot Classification | DeepAI Sep 4, 2023 - 09/04/23 - Cross-domain few-shot classification induces a much more challenging problem than its in-domain counterpart due to the existence o... few shot classificationfor crossadaptiveparametricprototype https://few-shot-text-classification.fastforwardlabs.com/ Few-Shot Text Classification An online research report on few-shot text classification by Cloudera Fast Forward. few shottextclassification https://sites.google.com/view/a-closer-look-at-few-shot A Closer Look at Few-shot Classification A Closer Look at Few-shot Classification ICLR 2019 a closer lookfew shotclassification https://arxiv.org/abs/2209.10250v1 [2209.10250v1] Query-Guided Networks for Few-shot Fine-grained Classification and Person Search Abstract page for arXiv paper 2209.10250v1: Query-Guided Networks for Few-shot Fine-grained Classification and Person Search https://openreview.net/forum?id=70_Wx-dON3q Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification | OpenReview A meta-dataset for few shot image classification multi domainfew shotimage classificationmetaalbum https://aclanthology.org/2020.coling-main.448/ Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks - ACL Anthology Trapit Bansal, Rishikesh Jha, Andrew McCallum. Proceedings of the 28th International Conference on Computational Linguistics. 2020. https://openreview.net/forum?id=PulKaNibeQ&referrer=%5Bthe%20profile%20of%20Deyu%20Meng%5D(%2Fprofile%3Fid%3D~Deyu_Meng1) Diversity-Enhanced and Classification-Aware Prompt Learning for Few-Shot Learning via Stable... Recent text-to-image generative models have exhibited an impressive ability to generate fairly realistic images from some text prompts. In this work, we... https://openreview.net/forum?id=VBXRMnRBfRF Metric Based Few-Shot Graph Classification | OpenReview We provide an overview of few-shot graph classification approaches, releasing a public codebase. We then propose adapting a metric learning approach to tackle... few shotmetricbasedgraphclassification https://aclanthology.org/2024.naacl-demo.18/ FastFit: Fast and Effective Few-Shot Text Classification with a Multitude of Classes - ACL Anthology Asaf Yehudai, Elron Bandel. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language... https://openreview.net/forum?id=rnfgk3iZrbc&referrer=%5BTasks%5D(/tasks) MGIMN: Multi-Grained Interactive Matching Network for Few-shot Text Classification | OpenReview Text classification struggles to generalize to unseen classes with very few labeled text instances per class. In such a few-shot learning (FSL) setting,... matching network