Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
Many large-scale Web applications that require ranked top-k retrieval are implemented using inverted indices. An inverted index represents a sparse term-document matrix, where non...
George Beskales, Marcus Fontoura, Maxim Gurevich, ...
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Since software systems are becoming increasingly more concurrent and distributed, modeling and analysis of interactions among their components is a crucial problem. In several app...
—In this paper we study the resource allocation in OFDM-based cognitive radio (CR) networks, under the consideration of many practical limitations such as imperfect spectrum sens...