I’m a third year PhD student in Harvard’s Theory of Computation and ML Theory groups. I’m advised by Leslie Valiant and supported by an NSF Graduate Research Fellowship. Previously, I undergraduated in math at Princeton.
I’m interested in theoretical computer science broadly. In particular, I study the interplay between algorithms, learning, and strategic behavior.
bedelman@g.harvard.edu | Google Scholar | he/him
News
Chara Podimata, Yo Shavit, and I organized a tutorial at FAccT 2021 called How to Achieve Both Transparency and Accuracy in Predictive Decision Making: An Introduction to Strategic Prediction!
Publications
Causal Strategic Linear Regression
with Yonadav Shavit and Brian Axelrod
ICML 2020
The Multiplayer Colonel Blotto Game
with Enric Boix-Adserà and Siddhartha Jayanti
EC 2020
SGD on Neural Networks Learns Functions of Increasing Complexity
with Preetum Nakkiran, Gal Kaplun, Dimitris Kalimeris, Tristan Yang, Fred Zhang, and Boaz Barak
NeurIPS 2019 (Spotlight)
Matrix Rigidity and the Croot-Lev-Pach Lemma
with Zeev Dvir
Theory of Computing, 2019