This paper quantifies the approximation error in Clark’s approach [1] to computing the maximum (max) of Gaussian random variables; a fundamental operation in statistical timing...
Fundamental to any graph cut segmentation methods is the assignment of edge weights. The existing solutions typically use gaussian, exponential or rectangular cost functions with ...
We describe a fast algorithm for Gabor filtering, specially designed for multi-scale image representations. Our proposal is based on three facts: first, Gabor functions can be de...
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
Neil D. Lawrence, John C. Platt, Michael I. Jordan
This paper describes the application of a Gaussian Estimation-of-Distribution (EDA) for real-valued optimization to the noisy part of a benchmark introduced in 2009 called BBOB (B...