In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
When selecting alternatives from large amounts of data, trade-offs play a vital role in everyday decision making. In databases this is primarily reflected by the top-k retrieval p...
Evaluation in Information Retrieval (IR) has long focused on effectiveness and efficiency. However, new and emerging access tasks now demand alternative evaluation measures which ...
Multiple instance learning (MIL) is a branch of machine learning that attempts to learn information from bags of instances. Many real-world applications such as localized content-...
With the large and increasing amount of visual information available in digital libraries and the Web, efficient and robust systems for image retrieval are urgently needed. In thi...