A Research Blog
For many of the famous open problems of theoretical computer science, most researchers agree on what the answer is, but the challenge is to prove it. Most complexity theorists (with few notable exceptions) believe that P≠NP, but we don't know how to prove it. Similarly, most people working on matrix multiplication believe that there is … Continue reading Obfuscation: The season 4 Finale
[Announcement from Jelani Nelson --Boaz]TL;DR: https://tinyurl.com/tcs-connections A task force has been convened by CATCS to investigate possibleapproaches to modifying aspects of the TCS community, especially ourpublishing culture, to enhance connections with other areas of CS andbe as welcoming as possible to a broad range of contributions withintheory. This committee will collect and synthesize feedback from … Continue reading Making TCS more connected / less insular
Galileo Galileo has many self-appointed intellectual heirs these days. Whether it's a claim that the election has been stolen, that COVID-19 is less fatal than the flu, that climate change or evolution are hoaxes, or that P=NP, we keep hearing from people considering themselves as bold truth-tellers railing against conventional wisdom. We are encouraged to … Continue reading On Galileo Galilei and “denialism” from elections to climate to COVID
[Guest post by Claire Vernade, Jessica Sorrell, Kamalika Chaudhuri, Lee Cohen, Mary Anne Smart, Michal Moshkovitz, and Ruth Urner. I am very happy about this initiative - mentoring and community is so important for success in science, and as I've written before, there is much work to do so women will have the same access … Continue reading Announcing the WiML-T Mentorship Program (guest post)
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
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
(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)
I am teaching deep learing 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 simple back-propagation and stochastic … Continue reading Yet another backpropagation tutorial
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
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)
