Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
In this chapter, we discuss a widely used fault-tolerant data replication model called virtual synchrony. The model responds to two kinds of needs. First, there is the practical qu...
While the problem of analyzing network traffic at the granularity of individual connections has seen considerable previous work and tool development, understanding traffic at a ...
In the framework of perfect loop nests with uniform dependences, tiling has been extensively studied as a source-to-source program transformation. Little work has been devoted to ...
In data centers hosting scaling Internet applications, operators face the tradeoff dilemma between resource efficiency and Quality of Service (QoS), and the root cause lies in wo...