[H/T Jelani Nelson] In recent years there has been increasing interest in using machinelearning to improve the performance of classical algorithms incomputer science, by fine-tuning their behavior to adapt to theproperties of the input distribution. This “data-driven” or“learning-based” approach to algorithm design has the potential tosignificantly improve the efficiency of some of the most widely … Continue reading Machine Learning for Algorithms – virtual workshop
Author: Boaz Barak
Causality and Fairness
Scribe notes by Junu Lee, Yash Nair, and Richard Xu. Previous post: Toward a theory of generalization learning Next post: TBD. See also all seminar posts and course webpage. lecture slides (pdf) - lecture slides (Powerpoint with animation and annotation) - video Much of the material on causality is taken from the wonderful book by … Continue reading Causality and Fairness
New seminar series in Simons Institute
The Simons institute started a new virtual seminar series highlighting recent advances in theoretical computer science. The first two talks in the series will be: June 16th 10am-11am PDT (1pm-2pm EDT). Virginia Vassilevska Williams on a Refined Laser Method and Faster Matrix MultiplicationAugust 5 10am-11am PDT (1pm-2pm EDT) Yuansi Chen on An Almost Constant Lower … Continue reading New seminar series in Simons Institute
Workshop on Local Algorithms (Guest post by Ronitt Rubinfeld)
The fifth WOLA (Workshop on Local Algorithms) will be virtual, and take place June 14-15. Registration is free, but required: please fill this form by June 10th to attend. Local algorithms — that is, algorithms that compute and make decisions on parts of the output considering only a portion of the input — have been studied in a number of … Continue reading Workshop on Local Algorithms (Guest post by Ronitt Rubinfeld)
STOC Test of time award
A reminder: the deadline to submit nominations for the STOC Test of Time Award is May 24. You can nominate papers for the 10 year award - STOC 2007-201120 year award - STOC 1997-200130 year award - STOC 1987-1991The award website ( https://sigact.org/prizes/stoc_tot.html ) helpfully contains links to the papers published in all these conferences. … Continue reading STOC Test of time award
Google Research Workshop on Deep Learning Theory
[Guest post from Pranjal Awasthi and Rina Panigrahy - workshop looks great! --Boaz] Please join us for a virtual Google workshop on “Conceptual Understanding of Deep Learning” When: May 17th 9am-4pm. Where: Live over Youtube, Goal: How does the Brain/Mind (perhaps even an artificial one) work at an algorithmic level? While deep learning has produced tremendous technological … Continue reading Google Research Workshop on Deep Learning Theory
Towards a Theory of Generalization in Reinforcement Learning: guest lecture by Sham Kakade
Scribe notes by Hamza Chaudhry and Zhaolin Ren Previous post: Natural Language Processing - guest lecture by Sasha Rush Next post: TBD. See also all seminar posts and course webpage. See also video of lecture. Lecture slides: Original form: main / bandit analysis. Annotated: main / bandit analysis. Sham Kakade is a professor in the … Continue reading Towards a Theory of Generalization in Reinforcement Learning: guest lecture by Sham Kakade
TCS Women Rising star nominations
(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
TCS summer school – call for TAs
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
Natural Language Processing (guest lecture by Sasha Rush)
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)
