Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
The interval discrimination task is a classical experimental paradigm that is employed to study working memory and decision making and typically involves four phases. First, the s...