"An Open Problem on Strongly Consistent Learning of the Best Prediction for Gaussian Processes"

entries per page

Filter:

Showing 1 to 20 of 100 entries

Book	Author(s)	Year	Publisher
Gaussian Processes for Machine Learning	Carl Edward Rasmussen; Christopher K. I. Williams	2005	MIT Press
Gaussian processes for machine learning	Carl Edward Rasmussen	2006	MIT Press
Gaussian Processes for Machine Learning	Carl Edward Rasmussen; Christopher K. I. Williams	2005	MIT Press,
Lectures on Gaussian Processes	Mikhail Lifshits	2012	Springer Berlin Heidelberg
Bayesian Reasoning and Gaussian Processes for Machine Learning Applications	Hemachandran K; Shubham Tayal; Preetha Mary George; Parveen Singla; Utku Kose	2022	Routledge
Gaussian Random Processes	I.A. Ibragimov; Y.A. Rozanov	1978	Springer New York
Organisation Structures and Processes: An Active Learning Approach (Open Learning Foundation)	The Open Learning Foundation	February 12, 1996	Wiley
Markov Processes, Gaussian Processes, and Local Times	Michael B. Marcus; Jay Rosen	2006-07	Cambridge University Press
A prediction interval for a first order Gaussian Markov process	Toke Jayachandran	1980	Naval Postgraduate School
Distance Learning: On the Design of an Open University	C.M. Chang; H.F.M Crombag; K.D.J.M. van der Drift; J.F. Moonen	1983	Springer Netherlands
Stochastic Analysis of Mixed Fractional Gaussian Processes	Yuliya Mishura and Mounir Zili	2018	Elsevier
Self-consistent Quantum-Field Theory and Bosonization for Strongly Correlated Electron Systems	Rudolf Haussmann	1999	Springer Berlin Heidelberg
Open Learning for Adults (Longman Open Learning Series)	Mary Thorpe; David Grugeon	July 13, 1987	Longman Information & Reference
Designing for Learning in an Open World	Gráinne Conole	2012	Springer New York
Prediction intervals for first order Markov processes	Tatiraju S. Murthy	1979	Naval Postgraduate School
Open Problems in Strongly Correlated Electron Systems	Janez Bonca; Peter Prelovsek; Anton Ramsak; Sarben Sarkar	2001	Springer Netherlands
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications	Vidyadhar S. Mandrekar; Leszek Gawarecki	2015	Routledge
Machine Learning for Microbial Phenotype Prediction	Roman Feldbauer	1st ed. 2016	Springer Fachmedien Wiesbaden
Conformal Prediction for Reliable Machine Learning	Vineeth Balasubramanian; Shen-Shyang Ho and Vladimir Vovk	2014	Morgan Kaufmann
Open Learning in the Mainstream (Open Learning)	Mary Thorpe; David Grugeon	January 4, 1995	Longman
Boook	Author(s)	Year	Publisher

Showing 1 to 20 of 100 entries

entries per page

Filter:

Showing 1 to 20 of 100 entries

Chapter	Author(s)	Book	Book Authors	Year	Publisher
An Open Problem on Strongly Consistent Learning of the Best Prediction for Gaussian Processes	László Györfi; Alessio Sancetta	Topics in Nonparametric Statistics: Proceedings of the First Conference of the International Society for Nonparametric Statistics	Michael G. Akritas; S. N. Lahiri; Dimitris N. Politis	2014	Springer New York
Best unbiased prediction for Gaussian and log-Gaussian processes		The First Erich L. Lehmann Symposium: Optimality (Institute of Mathematical Statistics: Lecture Notes - Monograph Series)	Javier Rojo, Victor Perez-Abreu	2004	Inst of Mathematical Statistic
An estimation problem for generalized Gaussian processes	Ognian Enchev	Stochastic Differential Systems: Proceedings of the IFIP-WG 7/1 Working Conference Eisenach, GDR, April 6–13, 1986	Hans Jürgen Engelbert; Wolfgang Schmidt	1987	Springer Berlin Heidelberg
75 Learning and prediction with Gaussian processes		Theory of Neural Information Processing Systems	A. C. C. Coolen, R. Kühn, P. Sollich	2005	Oxford University Press, USA
545 Prediction of Gaussian Processes		Machine learning for financial engineering	Györfi, László; Ottucsak, Gyorgy; Walk, Harro	2012	Imperial College Press
On-Line Learning Methods for Gaussian Processes	Shigeyuki Oba; Masa-aki Sato; Shin Ishii	Artificial Neural Networks - ICANN 2001: International Conference Vienna, Austria, August 21-25, 2001 Proceedings	Georg Dorffner; Horst Bischof; Kurt Hornik	2001	Springer Berlin Heidelberg
Strongly Consistent Mechanisms	Vladimir I. Danilov; Alexander I. Sotskov	Social Choice Mechanisms	Vladimir I. Danilov; Alexander I. Sotskov	2002	Springer Berlin Heidelberg
Strongly consistent representations	Bezalel Peleg; Hans Peters	Strategic Social Choice: Stable Representations of Constitutions	Bezalel Peleg; Hans Peters	2010	Springer Berlin Heidelberg
The periodic prediction problem for cyclostationary processes — an introduction	Sergio Bittanti	Modelling, Robustness and Sensitivity Reduction in Control Systems	Ruth F. Curtain	1987	Springer Berlin Heidelberg
MLP, Gaussian Processes and Negative Correlation Learning for Time Series Prediction	Waleed M. Azmy; Neamat El Gayar; Amir F. Atiya; Hisham El-Shishiny	Multiple Classifier Systems: 8th International Workshop, MCS 2009, Reykjavik, Iceland, June 10-12, 2009, Proceedings	Jón Atli Benediktsson; Josef Kittler; Fabio Roli	2009	Springer Berlin Heidelberg
On an open problem of Szasz	Jing-Wang Liu	Rings and radicals: proceedings of the International Conference, Shijiazhuang '94 /	Gardner, B. J.; Liu, Shaoxue.; Wiegandt, R.	1996.	Longman,
Sparse Gaussian Processes for Multi-task Learning	Yuyang Wang; Roni Khardon	Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part I	Peter A. Flach; Tijl De Bie; Nello Cristianini	2012	Springer Berlin Heidelberg
On the variation of Gaussian processes	Takayuki Kawada; Norio Kôno	Proceedings of the Second Japan-USSR Symposium on Probability Theory	G. Maruyama; Y. V. Prokhorov	1973	Springer Berlin Heidelberg
Strongly Consistent Detection for Nonparametric Hypotheses	László Györfi; Harro Walk	Measures of Complexity: Festschrift for Alexey Chervonenkis	Vladimir Vovk; Harris Papadopoulos; Alexander Gammerman	1st ed. 2015	Springer International Publishing
Gaussian Processes in Machine Learning	Carl Edward Rasmussen	Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003, Revised Lectures	Olivier Bousquet; Ulrike von Luxburg; Gunnar Rätsch	2004	Springer Berlin Heidelberg
Relational Learning with Gaussian Processes		Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference	Bernhard Schölkopf; John Platt; Thomas Hofmann	2007	MIT Press,
Learning Gradients with Gaussian Processes	Xinwei Jiang; Junbin Gao; Tianjiang Wang; Paul W. Kwan	Advances in Knowledge Discovery and Data Mining, Part II: 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010, Proceedings	Mohammed J. Zaki; Jeffrey Xu Yu; B. Ravindran; Vikram Pudi	2010	Springer Berlin Heidelberg
Lifelong Learning with Gaussian Processes	Christopher Clingerman; Eric Eaton	Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II	Michelangelo Ceci; Jaakko Hollmén; Ljupčo Todorovski; Celine Vens; Sašo Džeroski	1st ed. 2017	Springer International Publishing
Relational Learning with Gaussian Processes		Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference	Bernhard Schölkopf; John Platt; Thomas Hofmann	2007	MIT Press
Lectures on Gaussian Processes	Mikhail Lifshits	Lectures on Gaussian Processes	Mikhail Lifshits	2012	Springer Berlin Heidelberg
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

"An Open Problem on Strongly Consistent Learning of the Best Prediction for Gaussian Processes" - similar Books and Chapters