Abstract: We develop a framework for the distributed minimization of submodular functions. Submodular functions are a discrete analog of convex functions and are extensively used in large-scale ...

Abstract: We investigate the problem of maximizing the sum of submodular and supermodular functions under a fairness constraint. This sum function is non-submodular in general. For an offline model, ...

This project aims to reproduce the results of the paper titled "Streaming Algorithm for Monotone k-Submodular Maximization with Cardinality Constraints," published in ICML, 2022. The main goal of the ...

HER2-enriched breast cancer is a complex disease characterized by the overexpression of the ERBB2 amplicon. While the effects of this genomic aberration on the pathology have been studied, genome-wide ...

Critical for regulating cell function, integral membrane proteins (MPs) are key engineering targets. MP engineering is limited because these proteins are difficult to express with proper plasma ...

A k-submodular function is a generalization of a submodular function, where the input consists of k disjoint subsets, instead of a single subset, of the domain. Many machine learning problems, ...

The price of anarchy, defined as the ratio of the worst-case objective function value of a Nash equilibrium of a game and that of an optimal outcome, quantifies the inefficiency of selfish behavior.