Towards learning optimized kernels for complex Langevin

Locally Optimized Kernels

Support Vector Machines (SVM’s) with various kernels have become very successful in pattern classification and regression. However, single kernels do not lead to optimal data models. Replacing the input space by a kernel-based feature space in which the linear discrimination problem with margin maximization is solved is a general method that allows for mixing various kernels and adding new type...

Multiply - Add Optimized Fft Kernels

Modern computer architecture provides a special instruction|the fused multiply-add (FMA) instruction|to perform both a multiplication and an addition operation at the same time. In this paper newly developed radix-2, radix-3, and radix-5 FFT kernels that e ciently take advantage of this powerful instruction are presented. If a processor is provided with FMA instructions, the radix-2 FFT algorit...

Frame Kernels for Learning

The complex chemical Langevin equation.

The chemical Langevin equation (CLE) is a popular simulation method to probe the stochastic dynamics of chemical systems. The CLE's main disadvantage is its break down in finite time due to the problem of evaluating square roots of negative quantities whenever the molecule numbers become sufficiently small. We show that this issue is not a numerical integration problem, rather in many systems i...

Towards Real -Kernels

Do not cite! Do not copy! The-Kernel story is full of good ideas and blind alleys. The story began with high initial enthusiasm about the promised dramatic increase in exibility, safety and modularity. Over the years, this changed to disappointment because the rst-generation-kernels turned out to be ineecient and innexible. At present, we are observing radically new approaches to the-kernel ide...