hd20:start

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.**

hd20/start.txt · Last modified: 2020/12/22 13:04 by Nike Sun