Learning and testing in HD
Stochastic localization
Predicting and explaining statistical-computational gaps

SDP universality
Verifying communities
Glauber dynamics for SK
Algorithms for Ising perceptron
The Courtade-Kumar conjecture
Diameter of Gaussian polytopes

08/19-08/28 boot camp workshop: event page and reading resources
09/03 seminar Andrea Montanari: The interpolation phase transition in neural networks: memorization and generalization under lazy training
09/08 seminar Anindya De: Polynomial time trace reconstruction in the smoothed complexity model
09/14 RMK lecture Lenka Zdeborová: Insights on gradient-based algorithms in high-dimensional learning
09/15 seminar Mark Rudelson: Nodal domains of G(n,p) graphs
09/21-09/25 computational phase transitions workshop: event page
09/29 seminar Dana Ron: Distance approximation for graph properties
10/06 seminar Sam Hopkins: Robustly learning mixtures of (clusterable) gaussians via the SoS Proofs to Algorithms method
10/13 seminar Shiri Artstein: On (non-traditional) costs and potentials
10/19-10/23 concentration of measure workshop
10/27 seminar Elisabeth Werner: Thin-shell estimates for maximal affine surface area
11/03 seminar Yin Tat Lee: Work in progress: a structured sampling package
11/09 RMK lecture Ronitt Rubinfeld: Is your distribution In shape?
11/10 seminar Cris Moore: The planted matching problem
12/01 seminar Adam Klivans: Computational-statistical gaps for learning neural networks
12/08 seminar Amin Coja-Oghlan: Inference on random factor graphs
12/14-12/19 learning and testing workshop: event page
Seminar videos are available at this link.