<p>Few-short learning (FSL) can be useful for many (if not all) machine learning problems, including supervised learning (regression and classification) and reinforcement learning.</p>

<p>The paper <a href="https://arxiv.org/pdf/1904.05046.pdf" rel="nofollow noreferrer">Generalizing from a Few Examples: A Survey on Few-Shot Learning</a> (2020) provides an overview (including examples of applications and use cases) of FSL. Their definition of FSL provided is based on Tom Mitchell's famous definition of machine learning.</p>

<blockquote>
  <p>Definition 2.1 (<strong>Machine Learning</strong> [92, 94]). A computer program is said to learn from experience <span class="math-container">$E$</span> with respect to some classes of task <span class="math-container">$T$</span> and performance measure <span class="math-container">$P$</span> if its performance can improve with <span class="math-container">$E$</span> on <span class="math-container">$T$</span> measured by <span class="math-container">$P$</span>.</p>
</blockquote>

<p>Here's the definition of FSL.</p>

<blockquote>
  <p>Definition 2.2. <strong>Few-Shot Learning</strong> (FSL) is a type of machine learning problems, specified by <span class="math-container">$E$</span>, <span class="math-container">$T$</span> and <span class="math-container">$P$</span>, where <span class="math-container">$E$</span> contains only a limited number of examples with supervised information for the task <span class="math-container">$T$</span>.</p>
</blockquote>

<p>Specific examples of applications of FSL are</p>

<ul>
<li>character generation</li>
<li>drug toxicity discovery</li>
<li>sentiment classification from short text</li>
<li>object recognition</li>
</ul>

CC BY-SA 4.0
2020-05-17T11:23:21.260Z
2020-05-17T13:34:06.323Z
2020-05-17T13:34:06.323Z
nbro
<p>An interesting use case is IQ tests, or program synthesis from examples in general.</p>

<p>IQ tests often require you to derive a program from a few examples that can produce a certain output. See for instance <a href="https://github.com/fchollet/ARC" rel="nofollow noreferrer">https://github.com/fchollet/ARC</a></p>

CC BY-SA 4.0
2020-05-17T17:17:48.897Z
2020-05-17T17:17:48.897Z
apollo8
<p>Besides computer vision and image classification, what other use cases/applications are for few-shot learning?</p>

CC BY-SA 4.0
2020-05-17T06:35:04.243Z
Anything? A system which can learn from a single example is the holy grail.
FourierFlux
<machine-learning><reference-request><applications><few-shot-learning>
What are some use cases of few-shot learning?
etang
# What are some use cases of few-shot learning?

(Asked by: username_0 on 2020-05-17)

Besides computer vision and image classification, what other use cases/applications are for few-shot learning?

**Tags:** machine-learning, reference-request, applications, few-shot-learning

> **Comments:**
> **username_1**: Anything? A system which can learn from a single example is the holy grail.  

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## 2 answers

### Answer by username_2 on 2020-05-17. Score: 3

Few-short learning (FSL) can be useful for many (if not all) machine learning problems, including supervised learning (regression and classification) and reinforcement learning.

The paper [Generalizing from a Few Examples: A Survey on Few-Shot Learning](https://arxiv.org/pdf/1904.05046.pdf) (2020) provides an overview (including examples of applications and use cases) of FSL. Their definition of FSL provided is based on Tom Mitchell's famous definition of machine learning.

> Definition 2.1 (**Machine Learning** [92, 94]). A computer program is said to learn from experience $E$ with respect to some classes of task $T$ and performance measure $P$ if its performance can improve with $E$ on $T$ measured by $P$.

Here's the definition of FSL.

> Definition 2.2. **Few-Shot Learning** (FSL) is a type of machine learning problems, specified by $E$, $T$ and $P$, where $E$ contains only a limited number of examples with supervised information for the task $T$.

Specific examples of applications of FSL are

* character generation
* drug toxicity discovery
* sentiment classification from short text
* object recognition


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### Answer by username_3 on 2020-05-17. Score: 0

An interesting use case is IQ tests, or program synthesis from examples in general.

IQ tests often require you to derive a program from a few examples that can produce a certain output. See for instance <https://github.com/fchollet/ARC>


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