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02/02/2023
On the Efficacy of Differentially Private Few-shot Image Classification
There has been significant recent progress in training differentially pr...
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11/23/2022
Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners
This paper examines the robustness of deployed few-shot meta-learning sy...
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06/20/2022
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
Recent years have seen a growth in user-centric applications that requir...
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06/17/2022
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification
Modern deep learning systems are increasingly deployed in situations suc...
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07/02/2021
Memory Efficient Meta-Learning with Large Images
Meta learning approaches to few-shot classification are computationally ...
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04/08/2021
ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition
Object recognition has made great advances in the last decade, but predo...
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03/06/2020
TaskNorm: Rethinking Batch Normalization for Meta-Learning
Modern meta-learning approaches for image classification rely on increas...
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06/18/2019
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes
The goal of this paper is to design image classification systems that, a...
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05/24/2018
