Idan Mehalel
I am a direct-track, final year PhD student at the Computer Science department, Technion, where I am fortunate to be advised by Yuval Filmus and Shay Moran. I am working primarily on Foundations of Machine Learning. You can check out my c.v. here.
Contact information
Email: idanmehalel@gmail.com
Office: 513, Taub building, Computer Science department, Technion.
Updates
- I am talking at the Technion’s CS Theory semniar on February 14, at the HUJI Machine Learning club on February 15, and at the Technion’s Combinatorics seminar on February 21 (all dates are in 2024).
- I was honored to receive the Technion’s Computer Science department research excellence scholarship for Spring 2023 semester.
Preprints
Yuval Filmus, Steve Hanneke, Idan Mehalel and Shay Moran. Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs. Submitted.
Publications
Click the bullet for additional relevant links.
Idan Mehalel, Ananth Raman, Vinod Raman, Unique Subedi and Ambuj Tewari. Multiclass Online Learnability Under Bandit Feedback. ALT 2024.
Yuval Filmus and Idan Mehalel. Optimal sets of questions for Twenty Questions. SIAM Journal on Discrete Mathematics (SIDMA), 2024.
Yuval Filmus, Steve Hanneke, Idan Mehalel and Shay Moran. Optimal Prediction using Expeft Advice and Randomized Littlestone
DImension. COLT 2023.
Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel and Shay Moran. On Optimal Learning Under Targeted Data Poisoning. NeurIPS 2022.
Oral Presentation
Yuval FIlmus, Idan Mehalel and Shay Moran. A Resiliant Distributed Boosting Algorithm. ICML 2022.
Awards
- Technion Computer Science department research excellence scholarship, Spring 2023.
Teaching
- Logic for Computer Science (2022-2024)
- Topics in Machine Learning Theory (2021)
- Combinatorics for Computer Science (2019-2022)
Idan Mehalel 