Evolutionary computations and Word embeddings: Feature learning in NLP

I would like to welcome you all to the September meetup of KW Intersections. In this session we will have two talks. Justin Schonfield will talk about Evolutionary Computations and Mandy Gu from Kiite will talk about Word Embeddings. Also thank you very much for Kiite for sponsoring our pizza for the meetup.

Evolutionary Computation: What, When, and How? by Justin Schonfield

Evolutionary computation comprises a family of biologically inspired population based optimization techniques. This talk has two goals: to provide an overview of evolutionary computation and to dive a bit more deeply into the advantages and mechanics of these algorithms. The first part of the talk will provide an introduction to a few of the major approaches in evolutionary computation: genetic algorithms, genetic programming, and differential evolution among others. Showing how each technique works and when you might want to use it. The second part of this talk will look at fitness landscapes and discuss how evolutionary search can find robust solutions as well as the role representation plays in shaping these evolutionary search landscapes.

Word Embeddings: Feature Learning in NLP by Mandy Gu

"Word Embeddings" are a collection of methods used to map vocabulary words and phrases onto the set of real numbers. Ranging from methods rooted in deep learning, unsupervised learning to probabilistic modelling, these embeddings serve as the feature set for natural language processing.