Machine Learning for Algorithms – virtual workshop

[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

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)

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

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)