On the Benefits of Progressively Increasing Sampling Sizes in Stochastic Greedy Weak Submodular Maximization.
Abolfazl HashemiHaris VikaloGustavo de VecianaPublished in: IEEE Trans. Signal Process. (2022)
Keyphrases
- greedy algorithm
- objective function
- monte carlo
- point processes
- data sets
- metropolis hastings
- feature selection
- greedy algorithms
- search algorithm
- stochastic search
- jump diffusion process
- dynamic programming
- real time
- sample size
- reinforcement learning
- markov chain monte carlo
- information systems
- sampling strategies
- stochastic programming
- learning automata
- sampling algorithm
- hill climbing
- random sampling
- worst case
- upper bound
- lower bound