Recent Advances in High-dimensional Probability and Combinatorial Optimization

The speakers will cover recent advances in combinatorial optimization problems. The methods come from high-dimensional probability, often with inspiration from statistical physics. The session will address both static and algorithmic questions. To give a concrete example, several of the speakers have recent work on the perceptron model, from multiple viewpoints: one can ask about the geometry of the solution space (statics), or about the computational complexity of finding a solution given the disorder vectors as input (algorithmic). We expect that it will be fruitful to explore these multiple viewpoints in a combined session. All the proposed speakers have confirmed to me that they would be willing to participate. However, one of them, Marcus Michelen, has informed me that he has a scheduling conflict, and will only be available to attend on either August 2 or 3, so ideally the session could be scheduled for one of those days. If not, then I will need to find a replacement speaker. Additionally, depending on scheduling and balance of topics, Brice Huang and Mark Sellke can potentially give one joint talk rather than two separate talks.