taskGNU Astronomy Utilities - Tasks: task #15080, Machine learning in Gnuastro

 
 

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task #15080: Machine learning in Gnuastro

Submitted by:  Mohammad Akhlaghi <makhlaghi>
Submitted on:  Tue 30 Oct 2018 01:20:50 PM UTC  
 
Should Start On:  Mon 29 Oct 2018 11:00:00 PM UTC Should be Finished on:  Mon 29 Oct 2018 11:00:00 PM UTC
Category:  Libraries Priority:  5 - Normal
Item Group:  None Status:  In Progress
Privacy:  Public Percent Complete:  0%
Assigned to:  None Open/Closed:  Open
Effort:  0.00

Tue 30 Oct 2018 01:20:50 PM UTC, original submission:  

Machine learning libraries are increasingly being used in astronomy, or scientific applications in general. While it does have many caveats that must not be forgotten (see P.S.), it does also have benefits which can be useful. For example see arXiv:1810.10098 in task #14980.

I am starting this task for a general review of possible libraries (or generally, existing infra-structure) that we may be able to use in Gnuastro to enable Machine learning applications within Gnuastro's programs and libraries. Here the best summary list of libraries in various languages that I have found so far:

https://github.com/josephmisiti/awesome-machine-learning

We don't have to only look at those written in C. We can also link with libraries originally written in other languages, if they have a C interface. For example Torch is written in Lua, but they claim has an "amazing interface to C, via LuaJIT".

P.S. For a nice general discussion of Machine learning caveats see (link to YouTube) this talk by Ali Rahimi upon receiving the "Test-of-time" award at NIPS (Neural Information Processing Systems) 2017 conference. In this talk he compares Machine learning to alchemy. A (Facebook link) rebuttable was also published by Yann LeCun afterwards.

Mohammad Akhlaghi <makhlaghi>
Project Administrator

 

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