Guest post by Aviad Rubinstein and Matt Weinberg As explained in Boaz's previous posts [1] [2], the PhD admission process can be challenging for students who discover their passion for Theory of Computer Science late in their undergraduate studies. Discovering TCS earlier is especially challenging for students who aren't exposed to CS in high school, … Continue reading Updated Research Masters programs database by Aviad Rubinstein and Matt Weinberg
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Election insecurity
Election security has been studied for many years by computer scientists, but it is not as often that it attracts so much mainstream attention. I would never have expected to see my former Princeton colleague Andrew Appel on a Sean Hannity segment tweeted by President Trump. It may seem that even if it has partisan … Continue reading Election insecurity
MoPS and Junior-Senior Meeting (DISC 2020)
(Guest post by Shir Cohen and Mouna Safir) The 34th International Symposium on Distributed Computing (DISC 2020) was held on October 12-16, 2020, as a virtual conference. As such, the opportunity for community members to get to know each other in an informal environment was lacking. To address this need, we arranged two types of … Continue reading MoPS and Junior-Senior Meeting (DISC 2020)
Yet another backpropagation tutorial
(Updated and expanded 12/17/2021) I am teaching deep learning this week in Harvard's CS 182 (Artificial Intelligence) course. As I'm preparing the back-propagation lecture, Preetum Nakkiran told me about Andrej Karpathy's awesome micrograd package which implements automatic differentiation for scalar variables in very few lines of code. I couldn't resist using this to show how … Continue reading Yet another backpropagation tutorial
Digging into election models
With election on my mind, and constantly looking at polls and predictions, I thought I would look a little more into how election models are made. (Disclaimer: I am not an expert statistician / pollster and this is based on me trying to read their methodological description as well as looking into results of simulations … Continue reading Digging into election models
I’m with her (but 4 years too late)
In May 2016, after Donald Trump was elected as the republican nominee for president, I wrote the following blog post. I ended up not publishing it - this has always been a technical blog (and also more of a group blog, at the time). While the damage of a Donald Trump presidency was hypothetical at … Continue reading I’m with her (but 4 years too late)
Full-replica-symmetry-breaking based algorithms for dummies
One of the fascinating lines of research in recent years has been a convergence between the statistical physics and theoretical computer science points of view on optimization problems.`This blog post is mainly a note to myself (i.e., I'm the "dummy" 😃), trying to work out some basic facts in some of this line of work. … Continue reading Full-replica-symmetry-breaking based algorithms for dummies
Understanding generalization requires rethinking deep learning?
Yamini Bansal, Gal Kaplun, and Boaz Barak (See also paper on arxiv, code on gitlab, upcoming talk by Yamini&Boaz, video of past talk) A central puzzle of deep learning is the question of generalization. In other words, what can we deduce from the training performance of a neural network about its test performance on fresh … Continue reading Understanding generalization requires rethinking deep learning?
ITC 2021 (guest post by Benny Applebaum)
Following last year’s successful launch, we are happy to announce the second edition of the conference on Information-Theoretic Cryptography (ITC). The call for papers for ITC 2021 is out, and, to cheer you up during lockdowns, we prepared a short theme song https://youtu.be/kZT1icVoTp8 Feel free to add your own verse 😉 The submission deadline is … Continue reading ITC 2021 (guest post by Benny Applebaum)
SIGACT research highlights – call for nominations
TL;DR: Know of a great recent paper that should be highlighted to the theory community and beyond? Email a nomination to sigact.highlights.nominations@outlook.com by October 19th. The goal of the SIGACT Research Highlights Committee is to help promotetop computer science theory research via identifying results that are ofhigh quality and broad appeal to the general computer … Continue reading SIGACT research highlights – call for nominations
Windows On Theory 