New preprint up, led by Joy (Qiping) Yang and Yash Pote, with Jonathan Scarlett: we consider a relaxation of the standard (distribution) closeness testing task, where the algo now only needs to distinguish between p=q (equal) and |H(p)-H(q)|=Ω(1) (their entropies differ). 📝 ar…
Who's Who of AI
Clément Canonne
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
What they're sharing
[2605.23225] Entropy Equivalence Testing arxiv.org
arxiv.org
Articles & links
New preprint online: on multiple trade-offs b/w communication, sample, and randomness complexities for the fundamental task of Gaussian mean testing in a distributed setting. Led by the brilliant Nimitt (undergrad at IIT Gandhinagar) during a remote internship last year! 📝 arx…
Their own posts
Recent commentary
The OpenAI breakthrough on the unit distance problem seems genuinely impressive to my semi-layman eye. (It is!) One possible takeaway, though, is that if you throw an incredible amount of money and resources at focused research, there WILL be impressive progress. I wish we tried that, too.
"AI will replace U, they said" "Nothing yoai can do aboait it. It's the faitaire."
The Pope taking such a strong stance on AI feels rather unorthodox