Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Parallel file subsystems in today’s high-performance computers adopt many I/O optimization strategies that were designed for distributed systems. These strategies, for instance...
Wei-keng Liao, Kenin Coloma, Alok N. Choudhary, Le...
C applications, in particular those using operating system level services, frequently comprise multiple crosscutting concerns: network protocols and security are typical examples ...
Autonomic Computing is now showing its value as a solution to the increased complexities of maintaining computer systems and has been applied to many different fields. In this pap...
Achieving high performance in cryptographic processing is important due to the increasing connectivity among today’s computers. Despite steady improvements in microprocessor and...