I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
—We describe a system-level simulation model and show that it enables accurate predictions of both I/O subsystem and overall system performance. In contrast, the conventional app...
It is well known that optimal server placement is NP-hard. We present an approximate model for the case when both clients and servers are dense, and propose a simple server alloca...
The problem of indexing time series has attracted much interest. Most algorithms used to index time series utilize the Euclidean distance or some variation thereof. However, it has...
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...