In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
We propose a novel, non-simulative, probabilistic model for switching activity in sequential circuits, capturing both spatio-temporal correlations at internal nodes and higher ord...
Sanjukta Bhanja, Karthikeyan Lingasubramanian, N. ...
The quadratic relationship between voltage and energy has made dynamic voltage scaling (DVS) one of the most powerful techniques to reduce system power demands. Recently, techniqu...
Seokwoo Lee, Shidhartha Das, Toan Pham, Todd M. Au...
— This paper is interested in reward maximization of periodic real-time tasks under a given energy constraint, where the reward received depends on how much computation a task ru...