Abstract. In this paper, the Ssair (Semi-Supervised Active Image Retrieval) approach, which attempts to exploit unlabeled data to improve the performance of content-based image ret...
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...