
List of review articles on ML and AI that are on arXiv - painful
https://freenode-machinelearning.github.io/Resources/ArticlesReview.html#papers
======
Uehreka
This is at once an awesome and overwhelming list. Major kudos to whoever took
the time to put it together. I wonder if there’s a way to tag these or group
these into categories so that they’d be easier to bite into.

~~~
mlevental
it's auto-generated - it says so at the top. i don't see the point of this at
all since you could reproduce by simply searching "survey" or "introduction".
at minimum a cite count would've been helpful to distinguish well written ones
from poorly written ones

~~~
joker3
It'd be easy to split them by year or subject, as that's provided by the
arXiv.

~~~
painful
Just how is the subject provided by arXiv? By subject, do you mean the
categorization such as stat.ML, cs.AI, etc.?

~~~
mlevental
yea sure why not? like just a tiny bit more curation would've made this
actually useful. as it stands now it's just an unordered list.

~~~
painful
It's currently ordered by date, with most recent on top. It's not unordered.

------
theblackcat1002
I written a service recently which predict articles future citation from
arXiv, IEEE as rank which would save time from avoiding reading all the
articles. It's still a work in progress, especially the keyword filtering
part. link: [https://www.notify.institute/](https://www.notify.institute/)

~~~
iamantee
As Panoramix queried, could you introduce more details to your project? From
your website, I only got that you are analyzing paper based on the author info
and the citation history of his previous works and filtering papers by some
tech like topic modeling. Though the project is still in progress, will you
share info about what you have done and what you are about to do?

~~~
theblackcat1002
My model is based on these papers [1,2,3]. I found that adding the paper meta
info such as table count, page count improves my model performance ( R^2 score
of future citation of 2 years later ). For now, I am working on better
filtering method using word embedding, such that a keyword "CNN" would also
include papers about convolutional neural network.

1\. Xiao, Shuai et al. “On Modeling and Predicting Individual Paper Citation
Count over Time.” IJCAI (2016).

2\. Dong, Yuxiao et al. “Can Scientific Impact Be Predicted?” IEEE
Transactions on Big Data 2 (2016): 18-30.

3\. Yan, Rui et al. “Citation count prediction: learning to estimate future
citations for literature.” CIKM (2011).

------
gumby
Someone needs to work on the deep learning problem of automatically curating
these things and surfacing the important ones.

I suspect it's harder than the self driving car problem.

