DeepAI AI Chat
Log In Sign Up

The Signature Kernel

05/08/2023
by   Darrick Lee, et al.
0

The signature kernel is a positive definite kernel for sequential data. It inherits theoretical guarantees from stochastic analysis, has efficient algorithms for computation, and shows strong empirical performance. In this short survey paper for a forthcoming Springer handbook, we give an elementary introduction to the signature kernel and highlight these theoretical and computational properties.

READ FULL TEXT
01/23/2023

Sampling-based Nyström Approximation and Kernel Quadrature

We analyze the Nyström approximation of a positive definite kernel assoc...
04/04/2023

The insertion method to invert the signature of a path

The signature is a representation of a path as an infinite sequence of i...
06/26/2020

Computing the full signature kernel as the solution of a Goursat problem

Recently there has been an increased interested in the development of ke...
04/02/2023

Kernel-level Rootkit Detection, Prevention and Behavior Profiling: A Taxonomy and Survey

One of the most elusive types of malware in recent times that pose signi...
02/14/2012

Ensembles of Kernel Predictors

This paper examines the problem of learning with a finite and possibly l...
06/15/2020

Linear functional regression with truncated signatures

We place ourselves in a functional regression setting and propose a nove...
07/31/2022

Locating modifications in signed data for partial data integrity

We consider the problem of detecting and locating modifications in signe...