Rahul Patel
@Rpatel_15PhD Student @UofT | Interested in Discrete Optimization and ML | @polymtl, @Mila_Quebec, @AhdUniv alum
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Extremely happy to share that Neur2SP: Neural Two Stage Stochastic Program, joint work with @jsdumouchelle, @lyeskhalil and @meurevine got accepted at #NeurIPS2022. The journey of Neur2SP from a course project to #NeurIPS2022 was pretty exciting. [1/3]
Our next #robustoptimizationwebinar takes place this Friday, December 1, at 15:00 (CET). Speaker 1: @_estherjulien (TU Delft) Speaker 2: Justin Dumouchelle (University of Toronto) #ROW For more information check our webpage: lnkd.in/eujnAkBA
Thursday at 12pm Poster Session Neur2SP: Neural Two-Stage Stochastic Programming with Justin Dumouchelle, @Rpatel_15, @meurevine arxiv.org/abs/2205.12006 Train a ReLU network to approximate a complex expected value in a 2-stage stoch. program -> fast near-optimal solutions!
If you're at #NeurIPS2022 and interested in ML-for-Optimization, please check out my students and collaborators' poster presentations; a brief overview ⬇️
For those who are interested in learning more about decision diagrams for optimization, the ACP Winter School recordings are up! A great resource, with amazing tutorials and talks. youtube.com/playlist?list=…
I am excited to share my latest work: 8-bit optimizers – a replacement for regular optimizers. Faster 🚀, 75% less memory 🪶, same performance📈, no hyperparam tuning needed 🔢. 🧵/n Paper: arxiv.org/abs/2110.02861 Library: github.com/facebookresear… Video: youtube.com/watch?v=IxrlHA…
Biology's ImageNet moment has arrived: #AlphaFold2 solves Protein Folding at the #CASP14 competition! Blog: deepmind.com/blog/article/a…
Our paper "Pest management in cotton farms: an AI-system case study from the global South" has been accepted in KDD 2020. We describe a new solution for pest monitoring using AI & share the lessons we learned. 1/n 📰Paper: bit.ly/2EauyNT 📹Video: vimeo.com/443930632
co-at-work.zib.de Summer school on Mathematical Optimization with @mluebbecke @spokutta @69alodi @BDilkina @thor_koch @SparseRunner @pietroBelotti @leoneifler @hoppmannkai @swe_vie @GvncShn @sj_maher @pmchristophel @OliverBastert and many others. And me. 😉 Register now!
We released the code for SIREN! vsitzmann.github.io/siren We also wrote a comprehensive Colab notebook with a no-frills implementation that reproduces image, audio, and poisson experiments, and explores initialization- and shift-invariance properties! colab.research.google.com/github/vsitzma…
Almost done with the new website and docs for reveal.js. Here's a preview 👀 revealjs.netlify.app
#Python NaNs come from #Westworld. They cause me question the nature of my reality 😉 # weird ordering >>> sorted([5.0, math.nan, 10.0, 0.0]) [5.0, nan, 0.0, 10.0] >>> 3 < math.nan False >>> 3 > math.nan False # no commutativity >>> min(3, math.nan) 3 >>> min(math.nan, 3) nan
@lyeskhalil and I invite you to join us for DOTs, a virtual discrete optimization seminar series. The first DOT will take place next Tues, Apr 21 at 2pm with presentations by @HamedR_HR and Pierre Le Bodic. Visit our website talks.discreteopt.com to join our mailing list! #orms
Happy to find that the CS224w lecture on "Limitations of Graph Neural Networks" is out on YouTube. I helped making the slides :) The entire course is highly recommended for folks interested in graph ML! Video: youtube.com/watch?v=H6oOhE… Course website: web.stanford.edu/class/cs224w/
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