A Research Blog
(Guest post by Virginia Vassilevska Williams) Dear colleagues We invite you to nominate speakers for our TCS Women Rising Star talks at the TCS Women Spotlight Workshop at STOC 2021. To be eligible, your nominee has to be a theoretical computer science researcher (all topics represented at STOC are welcome) who is female or an … Continue reading TCS Women Rising star nominations
TL;DR: The summer school we are organizing is looking for TAs. Please forward this to your students as well as any departmental mailing lists. Are you passionate about teaching? Or about increasing diversity within TCS? If so, we need your help! The committee for advancement of theoretical computer science (CATCS) is organizing an online summer … Continue reading TCS summer school – call for TAs
Scribe notes by Benjamin Basseri and Richard Xu Previous post: Inference and statistical physics Next post: TBD. See also all seminar posts and course webpage. Alexander (Sasha) Rush is a professor at Cornell working in in Deep Learning / NLP. He applies machine learning to problems of text generation, summarizing long documents, and interactions between … Continue reading Natural Language Processing (guest lecture by Sasha Rush)
Scribe notes by Franklyn Wang Previous post: Robustness in train and test time Next post: Natural Language Processing (guest lecture by Sasha Rush). See also all seminar posts and course webpage. lecture slides (pdf) - lecture slides (Powerpoint with animation and annotation) - video Digression: Frequentism vs Bayesianism Before getting started, we'll discuss the difference … Continue reading Inference and statistical physics
Scribe notes by Praneeth Vepakomma Previous post: Unsupervised learning and generative models Next post: Inference and statistical physics. See also all seminar posts and course webpage. lecture slides (pdf) - lecture slides (Powerpoint with animation and annotation) - video In this blog post, we will focus on the topic of robustness - how well (or … Continue reading Robustness in train and test time
Shuchi Chawla, Madhur Tulsiani, and I are organizing a new summer school aimed at exposing undergraduate students to research directions in theoretical computer science and its applications. The school will take place from May 31 till June 4, 2021. This first iteration will be online, but we hope it will become a recurring and lasting event. … Continue reading New summer school in TCS
Scribe notes by Richard Xu Previous post: What do neural networks learn and when do they learn it Next post: TBD. See also all seminar posts and course webpage. lecture slides (pdf) - lecture slides (Powerpoint with animation and annotation) - video In this lecture, we move from the world of supervised learning to unsupervised … Continue reading Unsupervised Learning and generative models
Scribe notes by Manos Theodosis Previous post: A blitz through statistical learning theory Next post: Unsupervised learning and generative models. See also all seminar posts and course webpage. Lecture video - Slides (pdf) - Slides (powerpoint with ink and animation) In this lecture, we talk about what neural networks end up learning (in terms of … Continue reading What do deep networks learn and when do they learn it
Previous post: ML theory with bad drawings Next post: What do neural networks learn and when do they learn it, see also all seminar posts and course webpage. Lecture video (starts in slide 2 since I hit record button 30 seconds too late - sorry!) - slides (pdf) - slides (Powerpoint with ink and animation) … Continue reading A blitz through classical statistical learning theory
(Next post: Lecture 1 - a blitz through classical statistical learning theory . See also all seminar posts) This semester I am teaching a seminar on the theory of machine learning. For the first lecture, I would like to talk about what is the theory of machine learning. I decided to write this (very rough!) … Continue reading ML Theory with bad drawings
