Ridge regression is a classical statistical technique that attempts to address the bias-variance trade-off in the design of linear regression models. A reformulation of ridge regr...
—We investigate optimal resource allocation and power management in virtualized data centers with time-varying workloads and heterogeneous applications. Prior work in this area u...
Rahul Urgaonkar, Ulas C. Kozat, Ken Igarashi, Mich...
The prevailing approach to evaluating classifiers in the machine learning community involves comparing the performance of several algorithms over a series of usually unrelated data...
As we devise more complicated prior distributions, will inference algorithms keep up? We highlight a negative result in computable probability theory by Ackerman, Freer, and Roy (...
Quantitative steganalysis strives to estimate the change rate defined as the relative number of embedding changes introduced by steganography. In this paper, we propose two new cla...