Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. Active learning seeks to select the m...
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Understanding goals and preferences behind a user's online activities can greatly help information providers, such as search engine and E-Commerce web sites, to personalize c...
Honghua (Kathy) Dai, Lingzhi Zhao, Zaiqing Nie, Ji...
Abstract. When faced with the task of building accurate classifiers, active learning is often a beneficial tool for minimizing the requisite costs of human annotation. Traditional ...
In many networks, vertices have hidden attributes that are correlated with the network's topology. For instance, in social networks, people are more likely to be friends if t...