An Online Algorithm for Maximizing Submodular Functions
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Summary
An algorithm for solving a broad class of online resource allocation problems, applied in environments where abstract jobs arrive one at a time, and one can complete the jobs by investing time in a number of abstract activities, according to some schedule.
- Type
- report
- Published
- 2008-12-08
- Cited by
- 299
- References
- 31
- OpenAlex
- https://openalex.org/W2121671791
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:645814
Keywords
Submodular set function, Algorithm, Computer science, Mathematical optimization, Mathematics
References
- Restart Schedules for Ensembles of Problem Instances
- Greedy algorithms for on-line set-covering and related problems
- A Note on the Budgeted Maximization of Submodular Functions
- An analysis of approximations for maximizing submodular set functions—I
- A threshold of ln n for approximating set cover (preliminary version)
- Concentration Inequalities and Martingale Inequalities: A Survey
- Efficient sequences of trials
- Adaptive routing with end-to-end feedback: distributed learning and geometric approaches
- Learning diverse rankings with multi-armed bandits
- Learning with attribute costs
- A note on maximizing a submodular set function subject to a knapsack constraint
- How to use expert advice
- The weighted majority algorithm
- Playing games with approximation algorithms
- Maximizing the spread of influence through a social network
- An Economics Approach to Hard Computational Problems
- The Nonstochastic Multiarmed Bandit Problem
- The Budgeted Maximum Coverage Problem
- Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems
- Adaptive ordering of pipelined stream filters
Cited by
- Online Learning Techniques for Improving Robot Navigation in Unfamiliar Domains
- Selective Data Gathering in Community Sensor Networks
- Online submodular minimization
- Interactive Learning for Sequential Decisions and Predictions
- Anytime Prediction: Efficient Ensemble Methods for Any Computational Budget
- Efficient Optimization of Control Libraries
- Online algorithms for submodular minimization with combinatorial constraints
- Emergency maneuver library - ensuring safe navigation in partially known environments
- Predicting Contextual Sequences via Submodular Function Maximization
- Learning to rank from implicit feedback
- On the complexity of information planning in Gaussian models
- Online Learning of Assignments that Maximize Submodular Functions
- Approximation Algorithms for Bayesian Multi-Armed Bandit Problems
- Interactive Submodular Set Cover
- Contextual Sequence Prediction with Application to Control Library Optimization
- Knapsack Constrained Contextual Submodular List Prediction with Application to Multi-document Summarization
- Dynamic Resource Allocation in Conservation Planning
- Towards open ended learning: budgets, model selection, and representation
- Submodularity in Batch Active Learning and Survey Problems on Gaussian Random Fields
- Cascading Bandits: Learning to Rank in the Cascade Model
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