For 1d mean estimation when all we know is that variance is finite, does the median of means algorithm need to know an upper bound on the variance to get its guarantees? If yes, is there an algorithm that doesn't need to know this?
05.12.2024 05:44 — 👍 0 🔁 0 💬 0 📌 0
Interesting. I thought people had completely moved to ChatGPT/claude for this sort of stuff
28.11.2024 18:03 — 👍 1 🔁 0 💬 0 📌 0
I was surprised to see that 4th floor math/physics section has some very good textbooks!
25.11.2024 04:14 — 👍 1 🔁 0 💬 0 📌 0
What an honour. Congrats
24.11.2024 18:11 — 👍 1 🔁 0 💬 0 📌 0
Theoretical CS has it seems
24.11.2024 17:00 — 👍 1 🔁 0 💬 0 📌 0
Let’s tag @cosenal.bsky.social so he doesn’t miss out
24.11.2024 15:42 — 👍 1 🔁 0 💬 1 📌 0
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Senior Staff Research Scientist @Google DeepMind, previously Stats Prof @Oxford Uni - interested in Computational Statistics, Generative Modeling, Monte Carlo methods, Optimal Transport.
CS prof at Penn, Amazon Scholar in AWS. Interested in ML theory and related topics, as well as photography and Gilbert and Sullivan. Website: www.cis.upenn.edu/~mkearns
⛷️ ML Theorist carving equations and mountain trails | 🚴♂️ Biker, Climber, Adventurer | 🧠 Reinforcement Learning: Always seeking higher peaks, steeper walls and better policies.
https://ualberta.ca/~szepesva
Machine learning prof at U Toronto. Working on evals and AGI governance.
Working towards the safe development of AI for the benefit of all at Université de Montréal, LawZero and Mila.
A.M. Turing Award Recipient and most-cited AI researcher.
https://lawzero.org/en
https://yoshuabengio.org/profile/
Mathematician at UCLA. My primary social media account is https://mathstodon.xyz/@tao . I also have a blog at https://terrytao.wordpress.com/ and a home page at https://www.math.ucla.edu/~tao/
Associate professor at the University of Amsterdam and senior researcher at QuSoft working on quantum computing.
Mathematician working on probability and ML at U of Guelph in Canada. I also make math videos at https://youtube.com/@MihaiNicaMath
Post-doctoral Fellow @ Vector Institute, Toronto
Cosmologist, pilot, author, connoisseur of cosmic catastrophes. TEDFellow, CIFAR Azrieli Global Scholar. Domain verified through my personal astrokatie.com website. She/her. Dr.
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Senior Research Scientist at Google DeepMind. I ∈ Optimization ∩ Machine Learning. Fan of IronMaiden🤘.Here to discuss research 🤓
Virtual seminar series featuring the latest advances in theoretical reinforcement learning. Seminars (approximately) every Tuesday at 6pm UTC.
> https://sites.google.com/corp/view/rltheoryseminars
Associate Professor at CS UWaterloo
Machine Learning
Lab: opallab.ca
PhD student at University of Alberta. Interested in reinforcement learning, imitation learning, machine learning theory, and robotics
https://chanb.github.io/
wharton stats phd — ml theory, ml for science
prev: comp neuro, data, physics
working with Edgar Dobriban and Konrad Körding
also some sports (esp. philly! go birds)
cs phd @upenn advised by Michael Kearns, Aaron Roth, and Duncan Watts| previously @stanford | she/her
https://psamathe50.github.io/sikatasengupta/
RL Researcher | Postdoctoral Associate @mitidss
Interested in RL theory, stochastic optimisation and online learning.
https://muchay.github.io/
