The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
Multiagent Inductive Learning is the problem that groups of agents face when they want to perform inductive learning, but the data of interest is distributed among them. This pape...
Abstract. In [1], we presented a method for automatic detection of action items from natural conversation. This method relies on supervised classification techniques that are trai...
Statistical learning and probabilistic inference techniques are used to infer the hand position of a subject from multi-electrode recordings of neural activity in motor cortex. Fi...
Yun Gao, Michael J. Black, Elie Bienenstock, Shy S...