Non-Linear Matrix Completion for Social Image Tagging

Matrix Completion for Multi-label Image Classification

Recently, image categorization has been an active research topic due to the urgent need to retrieve and browse digital images via semantic keywords. This paper formulates image categorization as a multi-label classification problem using recent advances in matrix completion. Under this setting, classification of testing data is posed as a problem of completing unknown label entries on a data ma...

Non-negative matrix completion for action detection

Linear Bandits, Matrix Completion, and Recommendation Systems

The matrix completion paradigm has received much attention as a solution to the collaborative filtering problem in recommendation systems. The essential idea is that the user-by-item matrix of user preferences may be well modeled as a low rank matrix, and that this assumption may be used to impute unobserved entries, with good performance even when very few entries may be sampled from the matri...

Image Tag Completion by Noisy Matrix Recovery

It is now generally recognized that user-provided image tags are incomplete and noisy. In this study, we focus on the problem of tag completion that aims to simultaneously enrich the missing tags and remove noisy tags. The novel component of the proposed framework is a noisy matrix recovery algorithm. It assumes that the observed tags are independently sampled from an unknown tag matrix and our...

Can Social Tagging Improve Web Image Search?

Conventional Web image search engines can return reasonably accurate results for queries containing concrete terms, but the results are less accurate for queries containing only abstract terms, such as “spring” or “peace.” To improve the recall ratio without drastically degrading the precision ratio, we developed a method that replaces an abstract query term given by a user with a set of concre...