ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 0707.0303
  4. Cited By
Learning from dependent observations

Learning from dependent observations

Journal of Multivariate Analysis (JMA), 2007
2 July 2007
Ingo Steinwart
D. Hush
C. Scovel
ArXiv (abs)PDFHTML

Papers citing "Learning from dependent observations"

11 / 11 papers shown
Title
Rademacher learning rates for iterated random functions
Rademacher learning rates for iterated random functionsJournal of Complexity (JoC), 2025
Nikola Sandrić
114
0
0
16 Jun 2025
Improved Estimation of Relaxation Time in Non-reversible Markov Chains
Improved Estimation of Relaxation Time in Non-reversible Markov ChainsThe Annals of Applied Probability (Ann. Appl. Probab.), 2022
Geoffrey Wolfer
A. Kontorovich
347
10
0
01 Sep 2022
Universal Regression with Adversarial Responses
Universal Regression with Adversarial ResponsesAnnals of Statistics (Ann. Stat.), 2022
Moise Blanchard
Patrick Jaillet
161
6
0
09 Mar 2022
A Statistical Learning View of Simple Kriging
A Statistical Learning View of Simple KrigingTest (Madrid) (TM), 2022
Emilia Siviero
E. Chautru
Nathan Huet
218
0
0
15 Feb 2022
Learning from non-irreducible Markov chains
Learning from non-irreducible Markov chainsJournal of Mathematical Analysis and Applications (JMAA), 2021
Nikola Sandrić
Stjepan Šebek
OOD
100
2
0
08 Oct 2021
Adaptive Group Lasso Neural Network Models for Functions of Few
  Variables and Time-Dependent Data
Adaptive Group Lasso Neural Network Models for Functions of Few Variables and Time-Dependent DataSampling Theory, Signal Processing, and Data Analysis (SAMPTA), 2021
L. Ho
Nicholas Richardson
Giang Tran
242
3
0
24 Aug 2021
On Biased Random Walks, Corrupted Intervals, and Learning Under
  Adversarial Design
On Biased Random Walks, Corrupted Intervals, and Learning Under Adversarial DesignAnnals of Mathematics and Artificial Intelligence (AMAI), 2020
D. Berend
A. Kontorovich
L. Reyzin
Thomas Robinson
AAML
101
1
0
30 Mar 2020
High dimensional VAR with low rank transition
High dimensional VAR with low rank transitionStatistics and computing (Stat. Comput.), 2019
Pierre Alquier
Karine Bertin
P. Doukhan
Rémy Garnier
BDL
174
17
0
02 May 2019
Exponential inequalities for nonstationary Markov Chains
Exponential inequalities for nonstationary Markov Chains
Pierre Alquier
P. Doukhan
Xiequan Fan
204
10
0
27 Aug 2018
Statistical Learning Theory: Models, Concepts, and Results
Statistical Learning Theory: Models, Concepts, and Results
U. V. Luxburg
Bernhard Schölkopf
243
252
0
27 Oct 2008
Consistency of support vector machines for forecasting the evolution of
  an unknown ergodic dynamical system from observations with unknown noise
Consistency of support vector machines for forecasting the evolution of an unknown ergodic dynamical system from observations with unknown noiseAnnals of Statistics (AoS), 2007
Ingo Steinwart
Marian Anghel
481
9
0
02 Jul 2007
1