CVLGJan 12, 2016

Creativity in Machine Learning

arXiv:1601.03642v1
Originality Synthesis-oriented
AI Analysis

It serves as an introductory summary for newcomers to machine learning, offering starting points for understanding creative applications, but is incremental as it synthesizes existing work without new contributions.

The paper provides a high-level overview of how recent machine learning techniques can be modified to generate creative outputs such as images, text, and audio, which are novel and not trivial combinations of input data.

Recent machine learning techniques can be modified to produce creative results. Those results did not exist before; it is not a trivial combination of the data which was fed into the machine learning system. The obtained results come in multiple forms: As images, as text and as audio. This paper gives a high level overview of how they are created and gives some examples. It is meant to be a summary of the current work and give people who are new to machine learning some starting points.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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