The paper considers an interactive search paradigm in which at each round a user is presented with a set of k images and is required to select one that is closest to her target. P...
While query expansion techniques have been shown to improve retrieval performance in a centralized setting, they have not been well studied in a federated setting. In this paper, ...
User feedback is widely deployed in recent multimedia research to refine retrieval performance. However, most of the existing online learning algorithms handle interactions of a s...
Most users of machine-learning products are reluctant to use the systems without any sense of the underlying logic that has led to the system's predictions. Unfortunately many...
We present a new approach to the supervised learning of lateral interactions for the competitive layer model (CLM) dynamic feature binding architecture. The method is based on con...