We develop two simple interval-based models for dynamic superscalar processors. These models allow us to: i) predict with great accuracy performance and power consumption under va...
Abstract— This paper presents a new hierarchical segmentation of the observed driving behavioral data based on the levels of abstraction of the underlying dynamics. By synthesizi...
Ato Nakano, Hiroyuki Okuda, Tatsuya Suzuki, Shinki...
Digital image/video coding standards such as JPEG, H.264 are becoming more and more important for multimedia applications. Due to the huge amount of computations, there are signif...
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...
A hybrid learning neuro-fuzzy system with asymmetric fuzzy sets (HLNFS-A) is proposed in this paper. The learning methods of random optimization (RO) and least square estimation (...