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Kernel Autocovariance Operators of Stationary Processes: Estimation and
  Convergence

Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence

2 April 2020
Mattes Mollenhauer
Stefan Klus
Christof Schütte
P. Koltai
ArXivPDFHTML

Papers citing "Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence"

26 / 26 papers shown
Title
Optimal Rates for Regularized Conditional Mean Embedding Learning
Optimal Rates for Regularized Conditional Mean Embedding Learning
Zhu Li
Dimitri Meunier
Mattes Mollenhauer
Arthur Gretton
47
49
0
02 Aug 2022
Nonparametric approximation of conditional expectation operators
Nonparametric approximation of conditional expectation operators
Mattes Mollenhauer
P. Koltai
59
17
0
23 Dec 2020
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
Junhyung Park
Krikamol Muandet
54
80
0
10 Feb 2020
A Rigorous Theory of Conditional Mean Embeddings
A Rigorous Theory of Conditional Mean Embeddings
I. Klebanov
Ingmar Schuster
T. Sullivan
43
40
0
02 Dec 2019
High-probability bounds for the reconstruction error of PCA
High-probability bounds for the reconstruction error of PCA
Cassandra Milbradt
Martin Wahl
29
9
0
24 Sep 2019
Learning low-dimensional state embeddings and metastable clusters from
  time series data
Learning low-dimensional state embeddings and metastable clusters from time series data
Yifan Sun
Yaqi Duan
Hao Gong
Mengdi Wang
AI4TS
15
19
0
01 Jun 2019
A kernel-based approach to molecular conformation analysis
A kernel-based approach to molecular conformation analysis
Stefan Klus
A. Bittracher
Ingmar Schuster
Christof Schütte
30
26
0
28 Sep 2018
Counterfactual Mean Embeddings
Counterfactual Mean Embeddings
Krikamol Muandet
Motonobu Kanagawa
Sorawit Saengkyongam
S. Marukatat
CML
OffRL
44
39
0
22 May 2018
Approximation beats concentration? An approximation view on inference
  with smooth radial kernels
Approximation beats concentration? An approximation view on inference with smooth radial kernels
M. Belkin
77
69
0
10 Jan 2018
Concentration of weakly dependent Banach-valued sums and applications to
  statistical learning methods
Concentration of weakly dependent Banach-valued sums and applications to statistical learning methods
Gilles Blanchard
O. Zadorozhnyi
13
7
0
05 Dec 2017
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert
  Spaces
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces
Stefan Klus
Ingmar Schuster
Krikamol Muandet
53
121
0
05 Dec 2017
Variational approach for learning Markov processes from time series data
Variational approach for learning Markov processes from time series data
Hao Wu
Frank Noé
BDL
AI4TS
22
261
0
14 Jul 2017
Non-asymptotic upper bounds for the reconstruction error of PCA
Non-asymptotic upper bounds for the reconstruction error of PCA
M. Reiß
Martin Wahl
62
55
0
13 Sep 2016
Uncertain programming model for multi-item solid transportation problem
Uncertain programming model for multi-item solid transportation problem
Hasan Dalman
72
732
0
31 May 2016
Normal approximation and concentration of spectral projectors of sample
  covariance
Normal approximation and concentration of spectral projectors of sample covariance
V. Koltchinskii
Karim Lounici
43
70
0
28 Apr 2015
A Bernstein-type Inequality for Some Mixing Processes and Dynamical
  Systems with an Application to Learning
A Bernstein-type Inequality for Some Mixing Processes and Dynamical Systems with an Application to Learning
H. Hang
Ingo Steinwart
47
51
0
13 Jan 2015
Asymptotics and Concentration Bounds for Bilinear Forms of Spectral
  Projectors of Sample Covariance
Asymptotics and Concentration Bounds for Bilinear Forms of Spectral Projectors of Sample Covariance
V. Koltchinskii
Karim Lounici
102
90
0
20 Aug 2014
On the Complexity of Best Arm Identification in Multi-Armed Bandit
  Models
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models
E. Kaufmann
Olivier Cappé
Aurélien Garivier
112
1,021
0
16 Jul 2014
A useful variant of the Davis--Kahan theorem for statisticians
A useful variant of the Davis--Kahan theorem for statisticians
Yi Yu
Tengyao Wang
R. Samworth
64
571
0
04 May 2014
Hilbert Space Embeddings of Predictive State Representations
Hilbert Space Embeddings of Predictive State Representations
Byron Boots
Geoffrey J. Gordon
Arthur Gretton
74
95
0
26 Sep 2013
Fourier analysis of stationary time series in function space
Fourier analysis of stationary time series in function space
V. Panaretos
Shahin Tavakoli
44
144
0
09 May 2013
Dynamic Functional Principal Component
Dynamic Functional Principal Component
Siegfried Hormann
Łukasz Kidziński
Marc Hallin
83
202
0
26 Oct 2012
Hilbert Space Embeddings of POMDPs
Hilbert Space Embeddings of POMDPs
Yu Nishiyama
Abdeslam Boularias
Arthur Gretton
Kenji Fukumizu
62
52
0
16 Oct 2012
Modelling transition dynamics in MDPs with RKHS embeddings
Modelling transition dynamics in MDPs with RKHS embeddings
Steffen Grunewalder
Guy Lever
Luca Baldassarre
Massimiliano Pontil
Arthur Gretton
66
131
0
18 Jun 2012
Conditional mean embeddings as regressors - supplementary
Conditional mean embeddings as regressors - supplementary
Steffen Grunewalder
Guy Lever
Luca Baldassarre
Sam Patterson
Arthur Gretton
Massimiliano Pontil
102
144
0
21 May 2012
Weakly dependent functional data
Weakly dependent functional data
Siegfried Hormann
P. Kokoszka
58
360
0
05 Oct 2010
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