The Thirtieth Annual Conference on Neural Information Processing Systems (NIPS) is a multi-track machine learning and computational neuroscience conference that includes invited talks, demonstrations, symposia and oral and poster presentations of refereed papers. Following the conference, there are workshops which provide a less formal setting.

FlowMachines participates with the Workshop on “Constructive Machine Learning“.

In many real-world applications, machine learning algorithms constitute a tool of a ”constructive process”. These processes are similar to the general knowledge-discovery process but have a more specific goal. Such a goal is the construction of one-or-more domain elements with particular properties. In this workshop we want to bring together domain experts employing machine learning tools in constructive processes. We also intend to include machine learners investigating novel approaches or theories concerning constructive processes as a whole.

Interesting applications include image synthesis, drug and protein design, computational cooking. Moreover, and most interesting for FlowMachines, generation of art (paintings, music, poetry). Interesting approaches include deep generative learning, active approaches to structured output learning, transfer or multi-task learning of generative models, active search or online optimization over relational domains, and learning with constraints.

Many of the applications of constructive machine learning, including the ones mentioned above, are primarily considered in their respective application domain research area but are hardly present at machine learning conferences. By bringing together domain experts and machine learners working on constructive ML, we hope to bridge this gap between the communities.