2009/05/01 by Yogesh Girdhar, Gregory Dudek · 19 citations
Computer Science · Decision Sciences · Mathematics · #Advanced Bandit Algorithms Research #Algorithm #Artificial intelligence #Computer science #Computer vision #Data mining #Distributed Control Multi-Agent Systems #Generalization #Machine learning #Mathematical optimization #Mathematics #Online algorithm #Optimization and Search Problems #Sample (material) #Sampling (signal processing) #Secretary problem #Selection (genetic algorithm) #Sequence (biology) #Simple (philosophy)
paper · doi:10.1109/crv.2009.30
openalex publication_date 2009/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
The problem of online sampling of data, can be seen as a generalization of the classical secretary problem. The goal is to maximize the probability of picking the k highest scoring samples in our data, making the decision to select or reject a sample online. We present a new and simple online algorithm to optimally make this selection. We then apply this algorithm to a sequence of images taken by a mobile robot, with the goal of identifying the most interesting and informative images.