Four announcements (new positions and new papers)

A 4-in-1 post:

1. New PhD program in Data Science at NYU: http://cds.nyu.edu/phd-program/
2. New Moore-Sloan Data Science Fellow Position at NYU CDS: http://cds.nyu.edu/nyu-moore-sloan-data-science-fellows/
3. New Results on the Resilience of the Littlewood-Offord Problem: https://arxiv.org/abs/1609.08136
4. New Results on Optimality/Sub-optimality of PCA under Spike random matrix models: https://arxiv.org/abs/1609.05573

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Mathematics of Data Science course at NYU Courant

I am teaching a Mathematics of Data Science PhD level course at NYU Courant this Fall, I’ll be posting new Open Problems in this blog! See more info here.

SDP for Community Detection with many communities

I am happy to announce that there is significant progress on Open Problem 9.2. of my notes, in this paper Bruce Hajek, Yihong Wu, and Jiaming Xu show that, indeed, for communities, the natural Semidefinite Program is suboptimal!

Congratulations to the three!

 

Generalized Power Method for SO(2) Synchronization

More great news, this time about Open Problem 10.1. of Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science: Nicolas Boumal (who has contributed to this blog!) has made significant progress on this problem on his new paper.

Below the Kesten-Stigum bound for Community Detection

I have great news: There was (a lot) of progress on the Open Problem 9.1. of Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science in the last couple of weeks, independently by Emmanuel Abbe & Colin Sandon and by Jess Banks & Cristopher Moore.

Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science

The lecture notes for the course I gave this semester are now available here. Thanks to all the readers that gave me comments and feedback on the notes! I am sure the notes still contain many typos, if you find one, or have any general feedback, please let me know!

18.S096: Synchronization Problems and Alignment

The last set of Lecture notes for my course are now available here and are about Synchronization problems. They also include the last four open problems of the course. I will document the open problems here, while referring a much more detailed description of the problems on the notes, including description of partial progress.

18.S096: Compressed Sensing and Sparse Recovery

Another set of Lecture notes for my course, this time about Compressed Sensing and Sparse Recovery, is available here. As usual, I will document the open problems here, while referring to a much more detailed description of the problems on the notes, including description of partial progress.

18.S096: Max-Cut and Approximation Algorithms

The eight set of Lecture notes, now about Max Cut and Approximation Algorithms, is available here. They include five open problems, briefly documented here. Please see the notes for a lot more detail on the problems, relevant references and more.

18.S096: An extra Open Problem

I have just added an extra open problem (4.6.) to the fourth set of lecture notes. I am documenting it here.