This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Recent approaches to learning structured predictors often require approximate inference for tractability; yet its effects on the learned model are unclear. Meanwhile, most learnin...
Program errors are hard to detect and are costly both to programmers who spend significant efforts in debugging, and for systems that are guarded by runtime checks. Static verific...
This paper proposes a cycle accounting architecture for Simultaneous Multithreading (SMT) processors that estimates the execution times for each of the threads had they been execu...
A problem that is inherent to the development and efficient use of solvers is that of tuning parameters. The CP community has a long history of addressing this task automatically. ...