Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
Understanding the channel popularity or content popularity is an important step in the workload characterization for modern information distribution systems (e.g., World Wide Web,...
We introduce Hidden Process Models (HPMs), a class of probabilistic models for multivariate time series data. The design of HPMs has been motivated by the challenges of modeling h...
Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rus...
With power dissipation becoming an increasingly vexing problem across many classes of computer systems, measuring power dissipation of real, running systems has become crucial for...
We propose a class of alternative stochastic volatility models for electricity prices using the quantile function modeling approach. Specifically, we fit marginal distributions ...