The final sunset of #NIPS2013. Thanks Tahoe, you've been a great host. See everyone at the 7pm reception tonight. pic.twitter.com/wRX9iyr97m
— NIPS (@NipsConference) December 11, 2013
So NIPS2013 is finished, let's see what was interesting and picked by others:
Blog coverage:
- Sebastien Bubeck wrote a rather long entry on some NIPS presentations in A good NIPS!
- Hein talks about Zygmunt Zając who wrote about “13 NIPS Papers that caught our eye”
- Memming NIPS 2013
I also found these links of interest
As well as well as these tweets and their interesting links suggested on the #NIPS2013 tag on twitter (here is google docs list of all the tweets):
Animesh Garg @Animesh_Garg
Il Memming Park @memming
Suvash Sedhain @suvsh
brendan o'connor @brendan64
Notes on AdaGrad by Chris Dyer
Andreas Mueller @t3kcit
brendan o'connor @brendan64
.@brendan642 #NIPS2013
Shane Conway @statalgo
Alexandre Passos @atpassos_ml
Gilles Louppe @glouppe
Animesh Garg @Animesh_Garg
Richard @RichardSocher
Gilles Louppe @glouppe
Andreas Mueller @t3kcit
Olivier Grisel @ogrisel
Andreas Mueller @t3kcit
Chandra @sekhardrona
Dave Sullivan @_DaveSullivan
Dirk Gorissen @elazungu
Adam Stankiewicz @astankiew
eliana feasley @eli_awry
Chandra @sekhardrona
Michael Witbrock @witbrock
Tim van Erven @tverven
Erin LeDell @ledell
Erin LeDell @ledel
Join the CompressiveSensing subreddit or the Google+ Community and post there !
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As well as well as these tweets and their interesting links suggested on the #NIPS2013 tag on twitter (here is google docs list of all the tweets):
Animesh Garg @Animesh_Garg
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics ProgramsVikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum
Il Memming Park @memming
A simple example of Dirichlet process mixture inconsistency for the number of components[PDF]
Suvash Sedhain @suvsh
Deep content based recommendation #NIPS2013 http://media.nips.cc/nipsbooks/nipspapers/paper_files/nips26/1239.pdf … and my answer in Quora
brendan o'connor @brendan64
since i keep telling people at #nips2013 about @redpony's notes on adagrad, here they are, they are handy => http://www.ark.cs.cmu.edu/cdyer/adagrad.pdf …
Notes on AdaGrad by Chris Dyer
Andreas Mueller @t3kcit
Great tutorial by Rob Fergus on Deep Learning for Vision at #NIPS2013. Slides up soon, for now read their paper: http://arxiv.org/pdf/1311.2901v3.pdf …
brendan o'connor @brendan64
#NIPS2013 I really love Pearl's 2009 review http://ftp.cs.ucla.edu/pub/stat_ser/r350.pdf … I imagine this tutorial is hard to understand w/o reading that first ...
.@brendan642 #NIPS2013
.. also good are Cosma Shalizi's book chapters: http://www.stat.cmu.edu/~cshalizi/uADA/12/lectures/ch22.pdf … http://www.stat.cmu.edu/~cshalizi/uADA/12/lectures/ch23.pdf … http://www.stat.cmu.edu/~cshalizi/uADA/12/lectures/ch24.pdf …
Shane Conway @statalgo
"Approximate Dynamic Programming Finally Performs Well in the Game of Tetris" http://media.nips.cc/nipsbooks/nipspapers/paper_files/nips26/881.pdf … #ADP #NIPS2013
Alexandre Passos @atpassos_ml
New blog post: #NIPS2013 reading list http://atpassos.me/post/67560831508/nips-2013-reading-list …
Gilles Louppe @glouppe
My step for #OpenScience: code+demo for our #NIPS2013 paper "Understanding variable importances in random forests" https://github.com/glouppe/paper-variable-importances …
Animesh Garg @Animesh_Garg
Distributed Submodular Maximization: Simple effective and very few assumptions on functions win-win #NIPS2013 http://bit.ly/1gNBNVb
Richard @RichardSocher
Demo of our website to make machine learning for text classification easily accessible: http://etcml.com at #NIPS2013
Gilles Louppe @glouppe
Just presented "Scikit-Learn: Machine Learning in the Python ecosystem" at MLOSS #NIPS2013 Find the notebook at http://nbviewer.ipython.org/github/glouppe/talk-sklearn-mloss-nips2013/blob/master/oral/sklearn-mloss.ipynb …
Andreas Mueller @t3kcit
ClowdFlows looks like a great way to design data pipelines and do interactive exploration via the web http://www.clowdflows.org/ #NIPS2013
Olivier Grisel @ogrisel
Decision Jungles: memory efficient alternative to randomized trees http://papers.nips.cc/paper/5199-decision-jungles-compact-and-rich-models-for-classification … /cc @glouppe @pprett via @Chris_Said #NIPS2013
Andreas Mueller @t3kcit
As a consequence of #NIPS2013 I'm finally installing pylearn2 http://deeplearning.net/software/pylearn2/ … Probably the best way to get started with deep learning
Chandra @sekhardrona
Deep learning algorithms could make smart drugs http://goo.gl/Mm2Qq5 via @physorg_com #NIPS2013 #MachineLearning
Dave Sullivan @_DaveSullivan
FastML: 13 #NIPS2013 papers that caught our eye http://fastml.com/13-nips-papers-that-caught-our-eye/ …
Dirk Gorissen @elazungu
Interesting paper from #NIPS2013 "able to predict >95% of the weights of a deep NN without any drop in accuracy" http://media.nips.cc/nipsbooks/nipspapers/paper_files/nips26/1053.pdf …
Adam Stankiewicz @astankiew
NIPS 2013 Workshop on Data Driven Education http://lytics.stanford.edu/datadriveneducation/index.html#panel … #nips2013 via @jonathanhuang11
eliana feasley @eli_awry
Announced KA data sharing plans at #NIPS2013 . We're working on a whitepaper with more details, but initial info at http://khanacademy.org/r/research
Chandra @sekhardrona
explain my data: NIPS and the Zuckerberg Visit http://goo.gl/CrRbif #NIPS2013 #DeepLearning
Michael Witbrock @witbrock
My latest : Cyc and Semantic Construction Grammar #NIPS2013… on @slideshare http://www.slideshare.net/witbrock/cyc-and-semantic-construction-grammar-nips-2013-ket-workshop … via @SlideShare
Tim van Erven @tverven
Blog post: Wrote a PAC-Bayes mini-tutorial on the plane to #NIPS2013 to relate to standard concentration inequalities http://www.timvanerven.nl/blog/2013/12/pac-bayes-mini-tutorial-a-continuous-union-bound/ …joseph reisinger @josephreisinger
"Machine learning is a complex ecosystem"— Max Welling on the whole "Zuck at #nips2013" thing http://scientificpearlsofwisdom.blogspot.com/2013/12/i-was-conference-chair-for-nips-2013.html …
Erin LeDell @ledell
Now anyone that can query a database can do Bayesian inference http://probcomp.csail.mit.edu/bayesdb/index.html … #BayesDB
Dropout (neural networks/Geoffrey Hinton) as adaptive regularization in GLMs #NIPS2013 http://media.nips.cc/nipsbooks/nipspapers/paper_files/nips26/246.pdf …
Erin LeDell @ledel
Compressive feature learning can reduce text feature space by two orders of magnitude compared to k-grams #NIPS2013 http://media.nips.cc/nipsbooks/nipspapers/paper_files/nips26/1342.pdf …
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.
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