Autoencoder

By Prof. Seungchul Lee
http://iai.postech.ac.kr/
Industrial AI Lab at POSTECH

# 1. Unsupervised Learning¶

Definition

• Unsupervised learning refers to most attempts to extract information from a distribution that do not require human labor to annotate example
• Main task is to find the 'best' representation of the data

Dimension Reduction

• Attempt to compress as much information as possible in a smaller representation
• Preserve as much information as possible while obeying some constraint aimed at keeping the representation simpler

# 2. Autoencoders¶

It is like 'deep learning version' of unsupervised learning.

Definition

• An autoencoder is a neural network that is trained to attempt to copy its input to its output
• The network consists of two parts: an encoder and a decoder that produce a reconstruction

Encoder and Decoder

• Encoder function : $z = f(x)$
• Decoder function : $x = g(z)$
• We learn to set $g\left(f(x)\right) = x$