Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
With ever-increasing amounts of graph data from disparate sources, there has been a strong need for exploiting significant graph patterns with user-specified objective functions. ...
In many areas such as e-commerce, mission-critical N-tier applications have grown increasingly complex. They are characterized by non-stationary workloads (e.g., peak load several...
The current trend is for processors to deliver dramatic improvements in parallel performance while only modestly improving serial performance. Parallel performance is harvested th...
Sanjeev Kumar, Daehyun Kim, Mikhail Smelyanskiy, Y...
Address space randomization is an emerging and promising method for stopping a broad range of memory corruption attacks. By randomly shifting critical memory regions at process in...
Chongkyung Kil, Jinsuk Jun, Christopher Bookholt, ...