One-Shot Learning
92 papers with code • 1 benchmarks • 4 datasets
One-shot learning is the task of learning information about object categories from a single training example.
( Image credit: Siamese Neural Networks for One-shot Image Recognition )
Libraries
Use these libraries to find One-Shot Learning models and implementationsMost implemented papers
Ludwig: a type-based declarative deep learning toolbox
In this work we present Ludwig, a flexible, extensible and easy to use toolbox which allows users to train deep learning models and use them for obtaining predictions without writing code.
Typilus: Neural Type Hints
The network uses deep similarity learning to learn a TypeSpace -- a continuous relaxation of the discrete space of types -- and how to embed the type properties of a symbol (i. e. identifier) into it.
'Less Than One'-Shot Learning: Learning N Classes From M<N Samples
We propose the `less than one'-shot learning task where models must learn $N$ new classes given only $M<N$ examples and we show that this is achievable with the help of soft labels.
Active One-shot Learning
Recent advances in one-shot learning have produced models that can learn from a handful of labeled examples, for passive classification and regression tasks.
Learning to Remember Rare Events
We present a large-scale life-long memory module for use in deep learning.
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning
Humans and animals are capable of learning a new behavior by observing others perform the skill just once.
Generalization in Machine Learning via Analytical Learning Theory
This paper introduces a novel measure-theoretic theory for machine learning that does not require statistical assumptions.
Deep Reinforcement One-Shot Learning for Artificially Intelligent Classification Systems
Second, we develop the first open-source software for practical artificially intelligent one-shot classification systems with limited resources for the benefit of researchers in related fields.
A Deep One-Shot Network for Query-based Logo Retrieval
Logo detection in real-world scene images is an important problem with applications in advertisement and marketing.
Multimodal One-Shot Learning of Speech and Images
Imagine a robot is shown new concepts visually together with spoken tags, e. g. "milk", "eggs", "butter".