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Partial-monotone adaptive submodular maximization
Many AI/Machine learning problems require adaptively selecting a sequence of items, each selected item might provide some feedback that is valuable...
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Algorithms for Cardinality-Constrained Monotone DR-Submodular Maximization with Low Adaptivity and Query Complexity
Submodular maximization is a NP-hard combinatorial optimization problem regularly used in machine learning and data mining with large-scale data...
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Group fairness in non-monotone submodular maximization
Maximizing a submodular function has a wide range of applications in machine learning and data mining. One such application is data summarization...
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Constraint generation approaches for submodular function maximization leveraging graph properties
Submodular function maximization is an attractive optimization model and also a well-studied problem with a variety of algorithms available....
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Online non-monotone diminishing return submodular maximization in the bandit setting
In this paper, we study online diminishing return submodular (DR-submodular for short) maximization in the bandit setting. Our focus is on problems...
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Fast Parallel Algorithms for Submodular p-Superseparable Maximization
Maximizing a non-negative, monontone, submodular function \(f\) over...
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An optimal streaming algorithm for non-submodular functions maximization on the integer lattice
Submodular optimization problem has been concerned in recent years. The problem of maximizing submodular and non-submodular functions on the integer...
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Adaptive seeding for profit maximization in social networks
Social networks are becoming important dissemination platforms, and a large body of works have been performed on viral marketing, but most are to...
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Adaptive Algorithms on Maximizing Monotone Nonsubmodular Functions
Submodular optimization is widely used in large datasets. In order to speed up the problems solving, it is essential to design low-adaptive...
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Approximation guarantees for parallelized maximization of monotone non-submodular function with a cardinality constraint
Emerging applications in machine learning have imposed the problem of monotone non-submodular maximization subject to a cardinality constraint....
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Sequence submodular maximization meets streaming
In this paper, we study the problem of maximizing a sequence submodular function in the streaming setting, where the utility function is defined on...
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Submodular optimization problems and greedy strategies: A survey
The greedy strategy is an approximation algorithm to solve optimization problems arising in decision making with multiple actions. How good is the...
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Approximation algorithms for stochastic set cover and single sink rent-or-buy with submodular penalty
Stochastic combinatorial optimization problems are usually defined as planning problems, which involve purchasing and allocating resources in order...
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Price of dependence: stochastic submodular maximization with dependent items
In this paper, we study the stochastic submodular maximization problem with dependent items subject to downward-closed and prefix-closed constraints....
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Online learning under one sided \(\sigma \)-smooth function
The online optimization model was first introduced in the research of machine learning problems (Zinkevich, Proceedings of ICML, 928–936, 2003). It...
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Diversified-profit maximization in competitive social advertising
Due to the important role that social networks play in advertisements and propaganda, influence maximization (IM) problem which aims at finding some...
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Robust Budget Allocation Via Continuous Submodular Functions
The optimal allocation of resources for maximizing influence, spread of information or coverage, has gained attention in the past years, in...
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Siting renewable power generation assets with combinatorial optimisation
This paper studies the problem of siting renewable power generation assets using large amounts of climatological data while accounting for their...
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Adaptivity Gaps for the Stochastic Boolean Function Evaluation Problem
We consider the Stochastic Boolean Function Evaluation (SBFE) problem where the task is to efficiently evaluate a known Boolean function f on an...