Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
Data ambiguity is inherent in applications such as data integration, location-based services, and sensor monitoring. In many situations, it is possible to “clean”, or remove, ...
Reynold Cheng, Eric Lo, Xuan Yang, Ming-Hay Luk, X...
In the task of adaptive information filtering, a system receives a stream of documents but delivers only those that match a person's information need. As the system filters i...
Personalization is one of the important research issues in the areas of information retrieval and Web search. Providing personalized services that are tailored toward the specific...
Ka Cheung Sia, Shenghuo Zhu, Yun Chi, Koji Hino, B...
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...