165 citations · 1.6k across the 96 of their papers we have counts for
8 papers · 1 filter
Benchmarking optimality of time series classification methods in distinguishing diffusions
Zehong Zhang, Fei Lu, Esther Xu Fei +3
Statistical optimality benchmarking is crucial for analyzing and designing time series classification (TSC) algorithms. This study proposes to benchmark the optimality of TSC algor…
Signature Methods in Machine Learning
Terry Lyons, Andrew D. McLeod
Signature-based techniques give mathematical insight into the interactions between complex streams of evolving data. These insights can be quite naturally translated into numerical…
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes
Cristopher Salvi, Maud Lemercier, Chong Liu +3
Stochastic processes are random variables with values in some space of paths. However, reducing a stochastic process to a path-valued random variable ignores its filtration, i.e. t…
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
Maud Lemercier, Cristopher Salvi, Thomas Cass +3
Making predictions and quantifying their uncertainty when the input data is sequential is a fundamental learning challenge, recently attracting increasing attention. We develop Sig…
Labelling as an unsupervised learning problem
Terry Lyons, Imanol Perez Arribas
Unravelling hidden patterns in datasets is a classical problem with many potential applications. In this paper, we present a challenge whose objective is to discover nonlinear rela…
Sketching the order of events
Terry Lyons, Harald Oberhauser
We introduce features for massive data streams. These stream features can be thought of as "ordered moments" and generalize stream sketches from "moments of order one" to "ordered…