We consider the parallel complexity of submodular function minimization (SFM). We provide
a pair of methods which obtain two new query versus depth trade-offs a submodular function …

We initiate the study of matroid problems in a new oracle model called dynamic oracle. Our
algorithms in this model lead to new bounds for some classic problems, and a “unified” …

In this paper we study the problem of minimizing a submodular function f:2^V→R that is
guaranteed to have a k-sparse minimizer. We give a deterministic algorithm that computes …

In large-data applications, such as the inference process of diffusion models, it is desirable
to design sampling algorithms with a high degree of parallelization. In this work, we study …

We show how to use parallelization to speed up sampling from an arbitrary distribution µ on
a product space [q] n, given oracle access to counting queries: ℙ X∼ µ [XS= σ S] for any …

We consider the problem of query-efficient global max-cut on a weighted undirected graph
in the value oracle model examined by [RSW18]. This model arises as a natural special …

Abstract Matchings, Maximum Flow, and Matroid Intersections are fundamental
combinatorial optimization problems that have been studied extensively since the inception …

Many problems in discrete optimization can be succinctly encapsulated as the question of
minimizing a convex function ƒ, which captures the combinatorial structures of the problem …

In this talk, I will overview progress in our probabilistic understanding of the (shadow vertex)
simplex method in three different settings: smoothed polytopes (whose data is randomly …