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CS 263

Lectures

Lecture 1: Introduction

Wed, Sep 27, 3:00 pm – 4:20 pm

Lecture 2: Sampling vs. Counting

Mon, Oct 2, 3:00 pm – 4:20 pm

Lecture 3: Counting via Determinant; Intro to Markov Chains

Wed, Oct 4, 3:00 pm – 4:20 pm

Lecture 4: Markov Chain Mixing

Mon, Oct 9, 3:00 pm – 4:20 pm

Lecture 5: Mixing via Transport

Wed, Oct 11, 3:00 pm – 4:20 pm

Lecture 6: Dobrushin Influence Matrix

Mon, Oct 16, 3:00 pm – 4:20 pm

Lecture 7: Spectral Analysis

Wed, Oct 18, 3:00 pm – 4:20 pm

Lecture 8: Continuous Time

Mon, Oct 23, 3:00 pm – 4:20 pm

Lecture 9: Comparison Arguments

Wed, Oct 25, 3:00 pm – 4:20 pm

Lecture 10: Bipartite Perfect Matchings

Mon, Oct 30, 3:00 pm – 4:20 pm

Lecture 11: High-Dimensional Expanders

Wed, Nov 1, 3:00 pm – 4:20 pm

Lecture 12: Spectral Independence

Mon, Nov 6, 3:00 pm – 4:20 pm

Lecture 13: Log-Concave Polynomials

Wed, Nov 8, 3:00 pm – 4:20 pm

Lecture 14: Zeros of Polynomials

Mon, Nov 13, 3:00 pm – 4:20 pm

Lecture 15: Stability

Wed, Nov 15, 3:00 pm – 4:20 pm

Lecture 16: Correlation Decay

Mon, Nov 27, 3:00 pm – 4:20 pm

Lecture 17: Universality

Wed, Nov 29, 3:00 pm – 4:20 pm

Lecture 18: Stochastic Localization

Mon, Dec 4, 3:00 pm – 4:20 pm

Lecture 19: Continuous Sampling

Wed, Dec 6, 3:00 pm – 4:20 pm