We present a new online learning algorithm in the selective sampling framework, where labels must be actively queried before they are revealed. We prove bounds on the regret of ou...
Although most online learning environments are predominately text based, researchers have argued that representational support for the conceptual structure of a problem would addr...
Daniel D. Suthers, Ravi K. Vatrapu, Richard Medina...
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
—We consider a cognitive radio network with distributed multiple secondary users, where each user independently searches for spectrum opportunities in multiple channels without e...
Second order statistics have formed the basis of learning and adaptation due to its appeal and analytical simplicity. On the other hand, in many realistic engineering problems requ...