CODEWITHSUNDEEP
machine-learningprogramming-languagesnlplinguistics
IssamLaradji
IssamLaradji

Reputation: 6865

The intersection of Machine Learning and Programming Languages fields

While my research area is in Machine Learning (ML), I am required to take a project in Programming Languages (PL). Therefore, I'm looking to find a project that is inclined towards ML.

One intersection I know of between the two fields is Natural Language Processing (NLP), but I couldn't find concrete papers in that topic that are related to PL; perhaps due to my poor choice of keywords in the search query.

The main topics in the PL course are : Syntax & Symantics, Static Program Analysis, Functional Programming, and Concurrency and Logic programming

If you could suggest papers or keywords that are Machine Learning enthusiast friendly, that would be highly appreciated!

Upvotes: 0

Views: 897

Answers (3)

Ben Allison
Ben Allison

Reputation: 7394

I also happen to know that there's a project at the University of Edinburgh on using machine learning to analyse source code. Here's the first publication that came out of it

Upvotes: 1

Tom Palmer
Tom Palmer

Reputation: 462

Another very important intersection in these fields is probabilistic programming languages, which provide probabilistic inference over models specified as actual computer programs. It's a growing research field, including a recently started DARPA program on this topic.

Upvotes: 3

lejlot
lejlot

Reputation: 66785

If you are interested in NLP, then I would focus on two aspects of listed PL disciplines:

  • Syntax & Semantics - as this is incredibly closely realted to the NLP field, where in most cases the understanding is based on the various language grammars. Searching for papers regarding language modeling, information extraction, deep parsing would yield dozens of great research topics which are heavil related to the sytax/semantics problems.
  • logic programming -"in good old years" people believed that this is a future of AI, even though it is not (currently) true, it is still quite widely used forreasoning in some fields. In particular, prolog is a good example of language that can be used to reson (for example spatial-temporal reasoning) or even parse language (due to its "grammar like" productions).

If you wish to tackle some more ML related problem rather then NLP then you could focus on concurrency (parallelism) as it is very hot topic - making ML models more scalable, more efficient, "bigger, faster, stronger" ;) Just lookup keywords like GPU Machine Learning, large scale machine learning, scalable machine learning etc.

Upvotes: 2

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