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Recently, there has been an increased interest in the development of kernel methods for learning with sequential data.
A Course in Mathematical Analysis: pt. 2. Differential equations.[c1917
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A runge-kutta method for the numerical solution of the goursat problem in hyperbolic partial differential equations
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On the numerical solution for the goursat problem
A. M. Wazwaz · 1993
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The support vector method of function estimation
Vladimir Vapnik · 1998
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Differential equations driven by rough signals
Terry J Lyons · 1998
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Support vector machine classification and validation of cancer tissue samples using microarray expression data
Terrence S Furey, Nello Cristianini, Nigel Duffy, David W Bednarski, Michel Schummer, and David Haussler · 2000
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Support vector machine active learning with applications to text classification
Simon Tong and Daphne Koller · 2001
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Support vector machine active learning for image retrieval
Simon Tong and Edward Chang · 2001
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Special functions
George E. Andrews, Richard Askey, and Ranjan Roy · 2001
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Differential equations driven by rough paths
Terry Lyons, Michael Caruana, and Thierry Lévy · 2004
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Kernel methods for pattern analysis
John Shawe-Taylor, Nello Cristianini, et al · 2004
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Forecasting stock market movement direction with support vector machine
Wei Huang, Yoshiteru Nakamori, and Shou-Yang Wang · 2005
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A hilbert space embedding for distributions
Alex Smola, Arthur Gretton, Le Song, and Bernhard Schölkopf · 2007
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An extension theorem to rough paths
Terry Lyons and Nicolas Victoir · 2007
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Kernel methods in machine learning
Thomas Hofmann, Bernhard Schölkopf, and Alexander J Smola · 2008
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Time series prediction using support vector machines: a survey
Nicholas I Sapankevych and Ravi Sankar · 2009
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Super-samples from kernel herding
Yutian Chen, Max Welling, and Alex Smola · 2010
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Coropa computational rough paths (software library)
Terry Lyons et al · 2010
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Fast global alignment kernels
Marco Cuturi · 2011
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Convergence rates of inexact proximal-gradient methods for convex optimization
Mark Schmidt, Nicolas L Roux, and Francis R Bach · 2011
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On the equivalence between herding and conditional gradient algorithms
Francis R Bach, Simon Lacoste-Julien, and Guillaume Obozinski · 2012
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High order recombination and an application to cubature on wiener space
Christian Litterer, Terry Lyons, et al · 2012
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The iisignature library: efficient calculation of iterated-integral signatures and log signatures
Jeremy Reizenstein and Benjamin Graham · 2018
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Kernels for sequentially ordered data
Franz J Király and Harald Oberhauser · 2019
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Deep signature transforms
Patrick Kidger, Patric Bonnier, Imanol Perez Arribas, Cristopher Salvi, and Terry Lyons · 2019
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Using path signatures to predict a diagnosis of alzheimer’s disease
PJ Moore, TJ Lyons, J Gallacher, and Alzheimer’s Disease Neuroimaging Initiative · 2019
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Numerical method for model-free pricing of exotic derivatives in discrete time using rough path signatures
Terry Lyons, Sina Nejad, and Imanol Perez Arribas · 2019
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Optimization with sparsity-inducing penalties
Francis Bach, Rodolphe Jenatton, Julien Mairal, and Guillaume Obozinski · 2012
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Rough paths, signatures and the modelling of functions on streams
Terry Lyons · 2014
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Khalil Chouk and Massimiliano Gubinelli · 2014
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Handbook of Linear Partial Differential Equations for Engineers and Scientists
Andrei D. Polyanin and Vladimir E. Nazaikinskii · 2015
Cited alongside, same era.
Kernels for sequentially ordered data
Franz J Király and Harald Oberhauser · 2016
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Pricing under rough volatility
Christian Bayer, Peter Friz, and Jim Gatheral · 2016
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Belinda Tzen and Maxim Raginsky · 2019
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Utilization of the signature method to identify the early onset of sepsis from multivariate physiological time series in critical care monitoring
James H Morrill, Andrey Kormilitzin, Alejo J Nevado-Holgado, Sumanth Swaminathan, Samuel D Howison, and Terry J Lyons · 2020
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Bayesian learning from sequential data using gaussian processes with signature covariances
Csaba Toth and Harald Oberhauser · 2020
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Scalable gradients and variational inference for stochastic differential equations
Xuechen Li, Ting-Kam Leonard Wong, Ricky TQ Chen, and David K Duvenaud · 2020
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A generative adversarial network approach to calibration of local stochastic volatility models
Christa Cuchiero, Wahid Khosrawi, and Josef Teichmann · 2020
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A randomized algorithm to reduce the support of discrete measures
Francesco Cosentino, Harald Oberhauser, and Alessandro Abate · 2020
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Tslearn, a machine learning toolkit for time series data
Romain Tavenard, Johann Faouzi, Gilles Vandewiele, Felix Divo, Guillaume Androz, Chester Holtz, Marie Payne, Roman Yurchak, Marc Rußwurm, Kushal Kolar, and Eli Woods · 2020
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Distribution regression for continuous-time processes via the expected signature
Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin V Bonilla, and Terry Lyons · 2020
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Patrick Kidger and Terry Lyons · 2020
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Sk-tree: a systematic malware detection algorithm on streaming trees via the signature kernel
Thomas Cochrane, Peter Foster, Varun Chhabra, Maud Lemercier, Cristopher Salvi, and Terry Lyons · 2021
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Neural sdes as infinite-dimensional gans
Patrick Kidger, James Foster, Xuechen Li, Harald Oberhauser, and Terry Lyons · 2021
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