16 citations · 23 across the 12 of their papers we have counts for
13 papers
Multi-Agent Reinforcement Learning with Submodular Reward
Wenjing Chen, Chengyuan Qian, Shuo Xing +2
In this paper, we study cooperative multi-agent reinforcement learning (MARL) where the joint reward exhibits submodularity, which is a natural property capturing diminishing margi…
Bicriteria Algorithms for Submodular Cover with Partition and Fairness Constraints
Wenjing Chen, Yixin Chen, Victoria G. Crawford
In many submodular optimization applications, datasets are naturally partitioned into disjoint subsets. These scenarios give rise to submodular optimization problems with partition…
Fair Submodular Cover
Wenjing Chen, Shuo Xing, Samson Zhou +1
Submodular optimization is a fundamental problem with many applications in machine learning, often involving decision-making over datasets with sensitive attributes such as gender…
Linear Submodular Maximization with Bandit Feedback
Wenjing Chen, Victoria G. Crawford
Submodular optimization with bandit feedback has recently been studied in a variety of contexts. In a number of real-world applications such as diversified recommender systems and…
A Threshold Greedy Algorithm for Noisy Submodular Maximization
Wenjing Chen, Shuo Xing, Victoria G. Crawford
We consider the maximization of a submodular objective function , where the objective is not accessed as a value oracle but instead subject to nois…
Bicriteria Approximation Algorithms for the Submodular Cover Problem
Wenjing Chen, Victoria G. Crawford
In this paper, we consider the optimization problem Submodular Cover (SCP), which is to find a minimum cardinality subset of a finite universe such that the value of a submodul…
Scalable Bicriteria Algorithms for Non-Monotone Submodular Cover
Victoria G. Crawford
In this paper, we consider the optimization problem \scpl (\scp), which is to find a minimum cost subset of a ground set such that the value of a submodular function is abo…
An Efficient Evolutionary Algorithm for Minimum Cost Submodular Cover
Victoria G. Crawford
In this paper, the Minimum Cost Submodular Cover problem is studied, which is to minimize a modular cost function such that the monotone submodular benefit function is above a thre…
Faster Guarantees of Evolutionary Algorithms for Maximization of Monotone Submodular Functions
Victoria G. Crawford
In this paper, the monotone submodular maximization problem (SM) is studied. SM is to find a subset of size from a universe of size that maximizes a monotone submodular obj…
Submodular Cost Submodular Cover with an Approximate Oracle
Victoria G. Crawford, Alan Kuhnle, My T. Thai
In this work, we study the Submodular Cost Submodular Cover problem, which is to minimize the submodular cost required to ensure that the submodular benefit function exceeds a give…
Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
Alan Kuhnle, J. David Smith, Victoria G. Crawford +1
The optimization of submodular functions on the integer lattice has received much attention recently, but the objective functions of many applications are non-submodular. We provid…
Pseudo-Separation for Assessment of Structural Vulnerability of a Network
Alan Kuhnle, Tianyi Pan, Victoria G. Crawford +2
Based upon the idea that network functionality is impaired if two nodes in a network are sufficiently separated in terms of a given metric, we introduce two combinatorial \emph{pse…
An information theoretic formulation of the Dictionary Learning and Sparse Coding Problems on Statistical Manifolds
Rudrasis Chakraborty, Monami Banerjee, Victoria Crawford +1
In this work, we propose a novel information theoretic framework for dictionary learning (DL) and sparse coding (SC) on a statistical manifold (the manifold of probability distribu…