5 citations · 8 across the 5 of their papers we have counts for
5 papers
Curvature Beyond Positivity: Greedy Guarantees for Arbitrary Submodular Functions
Yixin Chen, Alan Kuhnle
Submodular functions -- functions exhibiting diminishing returns -- are central to machine learning. When the objective is monotone and non-negative, the greedy algorithm achieves…
Discretely Beyond : Guided Combinatorial Algorithms for Submodular Maximization
Yixin Chen, Ankur Nath, Chunli Peng +1
For constrained, not necessarily monotone submodular maximization, all known approximation algorithms with ratio greater than require continuous ideas, such as queries to the…
Scalable Distributed Algorithms for Size-Constrained Submodular Maximization in the MapReduce and Adaptive Complexity Models
Yixin Chen, Tonmoy Dey, Alan Kuhnle
Distributed maximization of a submodular function in the MapReduce (MR) model has received much attention, culminating in two frameworks that allow a centralized algorithm to be ru…
Approximation Algorithms for Size-Constrained Non-Monotone Submodular Maximization in Deterministic Linear Time
Yixin Chen, Alan Kuhnle
In this work, we study the problem of finding the maximum value of a non-negative submodular function subject to a limit on the number of items selected, a ubiquitous problem that…
Practical and Parallelizable Algorithms for Non-Monotone Submodular Maximization with Size Constraint
Yixin Chen, Alan Kuhnle
We present combinatorial and parallelizable algorithms for maximization of a submodular function, not necessarily monotone, with respect to a size constraint. We improve the best a…