We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Histograms are typically used to approximate data distributions. Histograms and related synopsis structures have been successful in a wide variety of popular database applications...
While process variations are becoming more significant with each new IC technology generation, they are often modeled via linear regression models so that the resulting performanc...
Xin Li, Jiayong Le, Padmini Gopalakrishnan, Lawren...
MAP queueing networks are recently proposed models for performance assessment of enterprise systems, such as multi-tier applications, where workloads are significantly affected b...
Abstract. We propose an online learning algorithm to tackle the problem of learning under limited computational resources in a teacher-student scenario, over multiple visual cues. ...