2019/05/30 by Alina Ene, Ene, Alina, Huy L. Nguyên +1 · 1 citation
Computer Science · #Complexity and Algorithms in Graphs #Cryptography and Data Security #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Optimization and Search Problems
paper · doi:10.48550/arxiv.1905.13272
openalex publication_date 2019/05/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
In this work, we give a new parallel algorithm for the problem of maximizing a non-monotone diminishing returns submodular function subject to a cardinality constraint. For any desired accuracy ε, our algorithm achieves a 1/e - ε approximation using O(logn log(1/ε) / ε3) parallel rounds of function evaluations. The approximation guarantee nearly matches the best approximation guarantee known for the problem in the sequential setting and the number of parallel rounds is nearly-optimal for any constant ε. Previous algorithms achieve worse approximation guarantees using Ω(log2n) parallel rounds. Our experimental evaluation suggests that our algorithm obtains solutions whose objective value nearly matches the value obtained by the state of the art sequential algorithms, and it outperforms previous parallel algorithms in number of parallel rounds, iterations, and solution quality.