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 [BibTeX] [Marc21]
An online framework for learning novel concepts over multiple cues
Type of publication: Conference paper
Citation: Luo_ACCV09
Booktitle: Proceeding of The 9th Asian Conference on Computer Vision
Year: 2009
Month: 9
Location: Xi'an, China
Abstract: We propose an online learning algorithm to tackle the problem of learning under limited computational resources in a teacher-student scenario, over multiple visual cues. For each separate cue, we train an online learning algorithm that sacrifices performance in favor of bounded memory growth and fast update of the solution. We then recover back performance by using multiple cues in the online setting. To this end, we use a two-layers structure. In the first layer, we use a budget online learning algorithm for each single cue. Thus, each classifier provides confidence interpretations for target categories. On top of these classifiers, a linear online learning algorithm is added to learn the combination of these cues. As in standard online learning setups, the learning takes place in rounds. On each round, a new hypothesis is estimated as a function of the previous one. We test our algorithm on two student-teacher experimental scenarios and in both cases results show that the algorithm learns the new concepts in real time and generalizes well.
Projects Idiap
Authors Luo, Jie
Orabona, Francesco
Caputo, Barbara
Added by: [UNK]
Total mark: 0
  • Luo_ACCV09_2009.pdf