Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...
The continual demand for greater performance and growing concerns about the power consumption in highperformance microprocessors make the branch predictor a critical component of ...
Highly efficient compression provides a promising approach to address the transmission and computation challenges imposed by moving object tracking applications on resource constra...
Rajib Kumar Rana, Wen Hu, Tim Wark, Chun Tung Chou