Sijing Tu

The other platform is much better now. Please join us.

The final draft of @BachFrancis's excellent new learning theory book is available: di.ens.fr/~fbach/ He doesn't cover VC dimension, but builds up from regression to general smooth losses, which is heresy of course, but actually fills a much-needed niche. Highly recommended!

@yu5k3 A classic ChatGPT answer!

Preparing my #defcon presentation: me> Can you draw the orange glasses from "Fear and Loathing in Las Vegas" onto my photo? ChatGPT> Download Image with Sunglasses Here me> 0_o #Friday

@StefanResearch Probably pretty standard techniques if you get a PhD in that area :)

TFW you read a paper from a different area and they briefly sketch the use of "standard techniques".

I am hiring for a student assistant (BSc/MSc student) to perform research & implementation tasks. The project is about data structures for data science algorithms. See the job ad below & please contact me if you have any questions. Deadline: August 29 jobs.tuwien.ac.at/Job/237423

The talk is now available from the link below. youtu.be/O2gpl5l2eQA?si…

MIT's lecture notes for "Probabilistic Methods in Combinatorics" A graduate-level introduction to the probabilistic method, a powerful technique in combinatorics and CS. ocw.mit.edu/courses/18-226…

DasGupta's inequality for normal random variables

Assistant professor position on algorithms and data analysis in KTH Royal Institute of Technology @KTHuniversity, funded by @WASP_Research. More details and online application: kth.varbi.com/en/what:job/jo… Deadline: May 3, 2024

Trying again - two post docs in learning theory under my supervision at Aarhus University are available deadline April 25th. Please share. au.dk/om/stillinger/…

Just accepted for publication at ACM CSUR our deep-dive into Densest Subgraph problem! 🎉 Funny project realized with a very cool team! 👨‍👨‍👦‍👦 It is a comprehensive source for those interested in graph optimization problems where the objective function is a notion of density 🕸️

Join my group in @KTHresearch! One PhD position funded by @WASP_Research. Application deadline Feb 29, 2024. More details at kth.se/lediga-jobb/69… #DataScience #MachineLearning #AI #AlgorithmsResearch

I'm looking for research assistants this semester to work on projects incl. data collection, analysis & running experiments to mitigate misinformation Ideal for third/final yr undergrads or masters students If you are interested please email me your CV or DM more below 👇

A random walk is Sₙ = X₁+⋯+Xₙ for IID sequence Xₙ. What is the probability that the first n terms are all negative? Interestingly, if Xₙ has a continuous and symmetric distribution, there is a simple answer which does not further depend on the distribution.

First week of fall classes at Stanford. I'm teaching a new MS-level class, Social Algorithms, w/ detailed syllabus here: msande231.github.io/syllabus Draws on syllabi by @5harad @msalganik @ashton1anderson & others. Input appreciated! Also, I'm now on the other place as jugander.

@jonassjuul Hi Jonas, may I ask will the presentations be uploaded to YouTube?

Talk info, including abstracts: David Lazer: aicentre.dk/events/talk-th… Jon Kleinberg: aicentre.dk/events/the-sci…

Two talks by legendary network scientists taking place in Copenhagen next week: David Lazer (Northeastern University/Harvard University), Monday 11am. Jon Kleinberg (Cornell University), Tuesday 3pm. Place: Aud 1, Gothersgade 140. See you there!

Talk title, David Lazer: "The emergent logic of the Online Information Ecosystem" Talk title, Jon Kleinberg: "The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization"

Tomorrow we will present another paper at #KDD2023: "Adversaries with Limited Information in the Friedkin–Johnsen Model" led by @SijingTu & joint with Aris @gionis. This is part of a bigger agenda to develop a theory for what is going in online social networks. Read on.⬇️⬇️⬇️

Our paper's full version: arxiv.org/abs/2306.10313

Our paper "Adversaries with Limited Information in the Friedkin-Johnsen Model" with Stefan @StefanResearch and Aris @gionis is out at KDD Proceedings (dl.acm.org/doi/10.1145/35…). I am super excited to meet and discuss with you at Long Beach. See you there soon! #KDD23