Making TCS more connected / less insular

[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

On Galileo Galilei and “denialism” from elections to climate to COVID

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

Announcing the WiML-T Mentorship Program (guest post)

[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)

Updated Research Masters programs database by Aviad Rubinstein and Matt Weinberg

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

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