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ORCIDNikolay I. Nikolaev
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2020 – today
- 2023
[c28]Evgueni N. Smirnov, Richard Delava, Ron Diris, Nikolay I. Nikolaev:
Multi-view Semi-supervised Learning Using Privileged Information. EANN 2023: 144-152
2010 – 2019
- 2019
- [j14]Nikolay Y. Nikolaev, Evgueni N. Smirnov, Daniel Stamate, Robert Zimmer:
A regime-switching recurrent neural network model applied to wind time series. Appl. Soft Comput. 80: 723-734 (2019) - 2015
- [c27]Firat Ismailoglu, Evgueni N. Smirnov, Nikolay Y. Nikolaev, Ralf Peeters
:
Instance-Based Decompositions of Error Correcting Output Codes. MCS 2015: 51-63 - 2014
- [c26]Nikolay Y. Nikolaev, Lilian M. de Menezes, Evgueni N. Smirnov:
Nonlinear filtering of asymmetric stochastic volatility models and Value-at-Risk estimation. CIFEr 2014: 310-317 - 2013
- [j13]Nikolay Y. Nikolaev, Georgi N. Boshnakov, Robert Zimmer:
Heavy-tailed mixture GARCH volatility modeling and Value-at-Risk estimation. Expert Syst. Appl. 40(6): 2233-2243 (2013) - [j12]Nikolay I. Nikolaev, Peter Tiño, Evgueni N. Smirnov:
Time-dependent series variance learning with recurrent mixture density networks. Neurocomputing 122: 501-512 (2013) - [c25]Evgueni N. Smirnov, Hua Zhang, Ralf Peeters, Nikolay I. Nikolaev, Maike Imkamp:
Aggregating Human-Expert Opinions for Multi-Label Classification. HCOMP (Works in Progress / Demos) 2013 - 2012
- [c24]Nikolay Y. Nikolaev, Evgueni N. Smirnov:
Analytical factor stochastic volatility modeling for portfolio allocation. CIFEr 2012: 1-8 - 2011
- [j11]Derrick Takeshi Mirikitani, Nikolay I. Nikolaev:
Nonlinear maximum likelihood estimation of electricity spot prices using recurrent neural networks. Neural Comput. Appl. 20(1): 79-89 (2011) - [c23]Nikolay I. Nikolaev, Peter Tiño, Evgueni N. Smirnov:
Time-Dependent Series Variance Estimation via Recurrent Neural Networks. ICANN (1) 2011: 176-184 - 2010
- [j10]Derrick Takeshi Mirikitani, Nikolay I. Nikolaev:
Efficient online recurrent connectionist learning with the ensemble Kalman filter. Neurocomputing 73(4-6): 1024-1030 (2010) - [j9]Derrick Takeshi Mirikitani, Nikolay I. Nikolaev:
Recursive Bayesian recurrent neural networks for time-series modeling. IEEE Trans. Neural Networks 21(2): 262-274 (2010) - [c22]Evgueni N. Smirnov, Nikolay I. Nikolaev, Georgi I. Nalbantov:
Single-Stacking Conformity Approach to Reliable Classification. AIMSA 2010: 161-170 - [c21]Nikolay Y. Nikolaev, Derrick Takeshi Mirikitani, Evgueni N. Smirnov:
Unscented grid filtering and elman recurrent networks. IJCNN 2010: 1-7 - [c20]Evgueni N. Smirnov, Georgi I. Nalbantov, Nikolay I. Nikolaev:
k-Version-Space Multi-class Classification Based on k-Consistency Tests. ECML/PKDD (3) 2010: 277-292
2000 – 2009
- 2008
- [j8]Nikolay Y. Nikolaev, Lilian M. de Menezes:
Sequential Bayesian kernel modelling with non-Gaussian noise. Neural Networks 21(1): 36-47 (2008) - [c19]Derrick Takeshi Mirikitani, Nikolay I. Nikolaev:
Recurrent Expectation Maximization Neural Modeling. CIMCA/IAWTIC/ISE 2008: 674-679 - [c18]Derrick Takeshi Mirikitani, Nikolay I. Nikolaev:
Dynamic Modeling with Ensemble Kalman Filter Trained Recurrent Neural Networks. ICMLA 2008: 843-848 - [c17]Evgueni N. Smirnov, Nikolay Y. Nikolaev, Georgi I. Nalbantov:
Description Identification and the Consistency Problem. SGAI Conf. 2008: 61-74 - 2007
- [c16]Nikolay Y. Nikolaev, Evgueni N. Smirnov:
A One-Step Unscented Particle Filter for Nonlinear Dynamical Systems. ICANN (1) 2007: 747-756 - [c15]Derrick Takeshi Mirikitani, Nikolay I. Nikolaev:
Recursive Bayesian Levenberg-Marquardt Training of Recurrent Neural Networks. IJCNN 2007: 282-287 - 2006
- [c14]Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, Nikolay I. Nikolaev:
Generalizing Version Space Support Vector Machines for Non-Separable Data. ICDM Workshops 2006: 744-748 - 2003
- [j7]Nikolay I. Nikolaev, Hitoshi Iba:
Polynomial harmonic GMDH learning networks for time series modeling. Neural Networks 16(10): 1527-1540 (2003) - [j6]Nikolay Y. Nikolaev, Hitoshi Iba:
Learning polynomial feedforward neural networks by genetic programming and backpropagation. IEEE Trans. Neural Networks 14(2): 337-350 (2003) - 2002
- [j5]Nikolay I. Nikolaev, Hitoshi Iba:
Genetic Programming of Polynomial Harmonic Networks Using the Discrete Fourier Transform. Int. J. Neural Syst. 12(5): 399-410 (2002) - [c13]Nikolay I. Nikolaev, Lilian M. de Menezes, Hitoshi Iba:
Overfitting avoidance in genetic programming of polynomials. IEEE Congress on Evolutionary Computation 2002: 1209-1214 - 2001
- [j4]Nikolay I. Nikolaev, Hitoshi Iba:
Accelerated Genetic Programming of Polynomials. Genet. Program. Evolvable Mach. 2(3): 231-257 (2001) - [j3]Nikolay I. Nikolaev:
Genetic Programming and Data Structures: Genetic Programming+Data Structures=Automatic Programming. Softw. Focus 2(4): 164-165 (2001) - [j2]Nikolay I. Nikolaev, Hitoshi Iba:
Regularization approach to inductive genetic programming. IEEE Trans. Evol. Comput. 5(4): 359-375 (2001) - [c12]Nikolay I. Nikolaev, Hitoshi Iba:
Genetic programming of polynomial harmonic models using the discrete Fourier transform. CEC 2001: 267-274 - [c11]Nikolay I. Nikolaev, Hitoshi Iba:
Genetic programming of polynomial harmonic models using the discrete Fourier transform. CEC 2001: 902-909
1990 – 1999
- 1999
- [c10]Nikolay I. Nikolaev, Hitoshi Iba:
Automated Discovery of Polynomials by Inductive Genetic Programming. PKDD 1999: 456-461 - 1998
- [j1]Nikolay I. Nikolaev, Vanio Slavov:
Inductive Genetic Programming with Decision Trees. Intell. Data Anal. 2(1-4): 31-44 (1998) - [c9]Nikolay I. Nikolaev, Vanio Slavov:
Concepts of Inductive Genetic Programming. EuroGP 1998: 49-59 - [c8]Vanio Slavov, Nikolay I. Nikolaev:
Genetic Algorithms, Fitness Sublandscapes and Subpopulations. FOGA 1998: 199-218 - [c7]Vanio Slavov, Nikolay I. Nikolaev:
Immune Network Dynamics for Inductive Problem Solving. PPSN 1998: 712-721 - 1997
- [c6]Nikolay I. Nikolaev, Vanio Slavov:
Inductive Genetic Programming with Decision Trees. ECML 1997: 183-190 - [c5]Vanio Slavov, Nikolay I. Nikolaev:
Fitness Landscapes and Inductive Genetic Programming. ICANNGA 1997: 414-418 - [c4]Vanio Slavov, Nikolay I. Nikolaev:
Inductive Genetic Programming and Superposition of Fitness Landscapes. ICGA 1997: 97-104 - 1996
- [c3]Nikolay I. Nikolaev, Evgueni N. Smirnov:
Stochastically Guided Disjunctive Version Space Learning. ECAI 1996: 443-447 - 1995
- [c2]Nikolay I. Nikolaev, Evgueni N. Smirnov:
Analytical Learning Guided by Empirical Technology: An Approach to Integration (Extended Abstract). ECML 1995: 327-330 - [c1]Evgueni N. Smirnov, Nikolay I. Nikolaev:
Multiple Explanation-based Learning Guided by Space Fragmenting. SCAI 1995: 85-96
Coauthor Index
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