In this recurring monthly feature, we filter recent research papers appearing on the arXiv.org
preprint server for compelling subjects relating to AI, machine
learning and deep learning – from disciplines including statistics,
mathematics and computer science – and provide you with a useful “best
of” list for the past month.
In this recurring monthly feature, we filter recent research papers appearing on the arXiv.org
preprint server for compelling subjects relating to AI, machine
learning and deep learning – from disciplines including statistics,
mathematics and computer science – and provide you with a useful “best
of” list for the past month. Researchers from all over the world
contribute to this repository as a prelude to the peer review process
for publication in traditional journals. arXiv contains a veritable
treasure trove of learning methods you may use one day in the solution
of data science problems. We hope to save you some time by picking out
articles that represent the most promise for the typical data
scientist. The articles listed below represent a fraction of all
articles appearing on the preprint server. They are listed in no
particular order with a link to each paper along with a brief
overview. Especially relevant articles are marked with a “thumbs up”
icon. Consider that these are academic research papers, typically
geared toward graduate students, post docs, and seasoned
professionals. They generally contain a high degree of mathematics so
be prepared.
Read more...
Happy reading!
Source: insideBIGDATA