![](https://dblp.uni-trier.de/img/logo.ua.320x120.png)
![](https://dblp.uni-trier.de/img/dropdown.dark.16x16.png)
![](https://dblp.uni-trier.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
![search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
default search action
Evgueni N. Smirnov
Person information
- affiliation (PhD): Maastricht University, Department of Data Science & Knowledge Engineering, The Netherlands
Refine list
![note](https://dblp.uni-trier.de/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
Journal Articles
- 2020
- [j13]Alex Gammerman, Vladimir Vovk
, Zhiyuan Luo, Evgueni N. Smirnov, Ralf Peeters
:
Special Issue on Conformal and Probabilistic Prediction with Applications. Neurocomputing 397: 264-265 (2020) - [j12]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers, Ralf Peeters
, Xi Wu:
Conformal Feature-Selection Wrappers and ensembles for negative-transfer avoidance. Neurocomputing 397: 309-319 (2020) - [j11]Firat Ismailoglu
, Rachel Cavill
, Evgueni N. Smirnov
, Shuang Zhou, Pieter Collins
, Ralf Peeters
:
Heterogeneous Domain Adaptation for IHC Classification of Breast Cancer Subtypes. IEEE ACM Trans. Comput. Biol. Bioinform. 17(1): 347-353 (2020) - 2019
- [j10]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) - 2017
- [j9]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers, Ralf Peeters
:
Conformal decision-tree approach to instance transfer. Ann. Math. Artif. Intell. 81(1-2): 85-104 (2017) - [j8]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers
, Ralf Peeters
:
Conformity-based source subset selection for instance transfer. Neurocomputing 258: 41-51 (2017) - [j7]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers
, Kurt Driessens
, Ralf Peeters
:
Testing exchangeability for transfer decision. Pattern Recognit. Lett. 88: 64-71 (2017) - 2015
- [j6]Shuang Zhou, Evgueni Nikolaevich Smirnov, Ralf Peeters
:
Conformal Region Classification with Instance-Transfer Boosting. Int. J. Artif. Intell. Tools 24(6): 1560002:1-1560002:25 (2015) - 2013
- [j5]Nikolay I. Nikolaev, Peter Tiño
, Evgueni N. Smirnov:
Time-dependent series variance learning with recurrent mixture density networks. Neurocomputing 122: 501-512 (2013) - 2009
- [j4]Stijn Vanderlooy, Ida G. Sprinkhuizen-Kuyper, Evgueni N. Smirnov, H. Jaap van den Herik:
The ROC isometrics approach to construct reliable classifiers. Intell. Data Anal. 13(1): 3-37 (2009) - [j3]Evgueni N. Smirnov, Georgi I. Nalbantov, A. M. Kaptein:
Meta-conformity approach to reliable classification. Intell. Data Anal. 13(6): 901-915 (2009) - 2004
- [j2]Evgueni N. Smirnov, H. Jaap van den Herik, Ida G. Sprinkhuizen-Kuyper:
A Unifying Version-Space Representation. Ann. Math. Artif. Intell. 41(1): 47-76 (2004) - 1998
- [j1]Evgueni N. Smirnov:
A Report on the ECAI-98 Conference from the Machine Learning Perspective. AI Commun. 11(3-4): 233-235 (1998)
Conference and Workshop Papers
- 2023
- [c60]Evgueni N. Smirnov:
Coverage vs Acceptance-Error Curves for Conformal Classification Models. COPA 2023: 534-545 - [c59]Evgueni N. Smirnov, Richard Delava, Ron Diris, Nikolay I. Nikolaev:
Multi-view Semi-supervised Learning Using Privileged Information. EANN 2023: 144-152 - [c58]Carla Wrede, Mark H. M. Winands, Evgueni N. Smirnov, Anna Wilbik
:
Towards Explainable Linguistic Summaries. FUZZ 2023: 1-6 - 2022
- [c57]Filip Schlembach
, Evgueni N. Smirnov, Irena Koprinska:
Conformal Multistep-Ahead Multivariate Time-Series Forecasting. COPA 2022: 316-318 - [c56]Husam Abdelqader, Evgueni N. Smirnov, Marc Pont
, Marciano Geijselaers:
Conformal Decision Rules. COPA 2022: 319-321 - [c55]Husam Abdelqader, Evgueni N. Smirnov, Marc Pont, Marciano Geijselaers:
Interpretable and Reliable Rule Classification Based on Conformal Prediction. PKDD/ECML Workshops (1) 2022: 385-401 - 2021
- [c54]William Lopez Jaramillo, Evgueni N. Smirnov:
Shapley-value based inductive conformal prediction. COPA 2021: 52-71 - [c53]Christie Courtnage, Evgueni N. Smirnov:
Shapley-Value Data Valuation for Semi-supervised Learning. DS 2021: 94-108 - 2020
- [c52]Zachary Warnes, Magnus Kinder, Evgueni N. Smirnov:
Course Recommender Systems with Statistical Confidence. EDM 2020 - [c51]Raphaël Morsomme, Evgueni N. Smirnov:
Valid Prediction Intervals for Course Grades with Conformal Prediction. ICMLA 2020: 936-941 - 2019
- [c50]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers:
Ensembles based on conformal instance transfer. COPA 2019: 23-42 - [c49]Raphaël Morsomme, Evgueni N. Smirnov:
Conformal Prediction for Students' Grades in a Course Recommender System. COPA 2019: 196-213 - 2018
- [c48]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers, Ralf Peeters, Tao Jiang:
Conformal feature-selection wrappers for instance transfer. COPA 2018: 96-113 - [c47]Jelmer Neeven, Evgueni N. Smirnov:
Conformal stacked weather forecasting. COPA 2018: 220-233 - [c46]Dorian Beganovic, Evgueni N. Smirnov:
Ensemble Cross-Conformal Prediction. ICDM Workshops 2018: 870-877 - [c45]Florian Van Daalen
, Evgueni N. Smirnov, Nasser Davarzani, Ralf Peeters, Joël M. H. Karel
, Hans-Peter Brunner-La Rocca
:
An Ensemble Approach to Time Dependent Classification. ICMLA 2018: 1007-1011 - [c44]Firat Ismailoglu, Evgueni N. Smirnov, Ralf Peeters, Shuang Zhou, Pieter Collins
:
Heterogeneous Domain Adaptation Based on Class Decomposition Schemes. PAKDD (1) 2018: 169-182 - 2017
- [c43]Fabian Braun, Olivier Caelen, Evgueni N. Smirnov, Steven Kelk, Bertrand Lebichot:
Improving Card Fraud Detection Through Suspicious Pattern Discovery. IEA/AIE (2) 2017: 181-190 - [c42]Kurt Driessens
, Irena Koprinska, Olga C. Santos
, Evgueni N. Smirnov, Kalina Yacef
, Osmar R. Zaïane:
UMAP 2017 EdRecSys Workshop Organizers' Welcome & Organization. UMAP (Adjunct Publication) 2017: 125-127 - [c41]Mara Houbraken, Chang Sun, Evgueni N. Smirnov, Kurt Driessens
:
Discovering Hidden Course Requirements and Student Competences from Grade Data. UMAP (Adjunct Publication) 2017: 147-152 - 2016
- [c40]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers
, Ralf Peeters
:
Decision Trees for Instance Transfer. COPA 2016: 116-127 - [c39]Nasser Davarzani, Ralf Peeters, Evgueni N. Smirnov, Joël M. H. Karel
, Hans-Peter Brunner-La Rocca
:
Ranking Accuracy for Logistic-GEE Models. IDA 2016: 14-25 - 2015
- [c38]Shuang Zhou, Gijs Schoenmakers, Evgueni N. Smirnov, Ralf Peeters, Kurt Driessens, Siqi Chen:
Largest Source Subset Selection for Instance Transfer. ACML 2015: 423-438 - [c37]Firat Ismailoglu, Evgueni N. Smirnov, Ralf Peeters
:
Conformal ECOC Machines. ICTAI 2015: 361-368 - [c36]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers, Ralf Peeters
, Kurt Driessens
:
A Non-parametric Conformity-Based Test for Transfer Decisions. ICTAI 2015: 628-635 - [c35]Firat Ismailoglu, Ida G. Sprinkhuizen-Kuyper, Evgueni N. Smirnov, Sergio Escalera
, Ralf Peeters
:
Fractional Programming Weighted Decoding for Error-Correcting Output Codes. MCS 2015: 38-50 - [c34]Firat Ismailoglu, Evgueni N. Smirnov, Nikolay Y. Nikolaev, Ralf Peeters
:
Instance-Based Decompositions of Error Correcting Output Codes. MCS 2015: 51-63 - 2014
- [c33]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 - [c32]Elena Mocanu
, Decebal Constantin Mocanu
, Haitham Bou-Ammar, Zoran Zivkovic, Antonio Liotta
, Evgueni N. Smirnov:
Inexpensive user tracking using Boltzmann Machines. SMC 2014: 1-6 - 2013
- [c31]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 - [c30]Shuang Zhou, Evgueni N. Smirnov, Haitham Bou-Ammar, Ralf Peeters:
Conformity-Based Transfer AdaBoost Algorithm. AIAI 2013: 401-410 - 2012
- [c29]Nikolay Y. Nikolaev, Evgueni N. Smirnov:
Analytical factor stochastic volatility modeling for portfolio allocation. CIFEr 2012: 1-8 - [c28]Alexandru Surpatean, Evgueni N. Smirnov, Nicolai Manie:
Master Orientation Tool. ECAI 2012: 995-996 - [c27]Alexandru Surpatean, Evgueni N. Smirnov, Nicolai Manie:
Similarity Functions for Collaborative Master Recommendations. EDM 2012: 230-231 - 2011
- [c26]Nikolay I. Nikolaev, Peter Tiño
, Evgueni N. Smirnov:
Time-Dependent Series Variance Estimation via Recurrent Neural Networks. ICANN (1) 2011: 176-184 - [c25]Georgi I. Nalbantov, Andre Dekker
, Dirk De Ruysscher, Philippe Lambin, Evgueni N. Smirnov:
The Combination of Clinical, Dose-Related and Imaging Features Helps Predict Radiation-Induced Normal-Tissue Toxicity in Lung-cancer Patients - An in-silico Trial Using Machine Learning Techniques. ICMLA (2) 2011: 220-224 - 2010
- [c24]Evgueni N. Smirnov, Nikolay I. Nikolaev, Georgi I. Nalbantov:
Single-Stacking Conformity Approach to Reliable Classification. AIMSA 2010: 161-170 - [c23]Georgi I. Nalbantov, Evgueni N. Smirnov:
Soft Nearest Convex Hull Classifier. ECAI 2010: 841-846 - [c22]Nikolay Y. Nikolaev, Derrick Takeshi Mirikitani, Evgueni N. Smirnov:
Unscented grid filtering and elman recurrent networks. IJCNN 2010: 1-7 - [c21]Georgi I. Nalbantov, Evgueni N. Smirnov, Dilyan I. Nalbantov, Gerhard Weiss, Karl Nienhaus, Manuel Warcholik, Fiona Mavroudis:
Image Mining for Intelligent Autonomous Coal Mining. ICDM (Poster and Industry Proceedings) 2010: 17-23 - [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 - 2009
- [c19]Matthijs Moed, Evgueni N. Smirnov:
Efficient AdaBoost Region Classification. MLDM 2009: 123-136 - 2008
- [c18]J. van Prehn, Evgueni N. Smirnov:
Region Classification with Decision Trees. ICDM Workshops 2008: 53-59 - [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 - 2006
- [c15]Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, Georgi I. Nalbantov, Stijn Vanderlooy:
Version Space Support Vector Machines. ECAI 2006: 809-810 - [c14]Evgueni N. Smirnov, Stijn Vanderlooy, Ida G. Sprinkhuizen-Kuyper:
Meta-Typicalness Approach to Reliable Classification. ECAI 2006: 811-812 - [c13]Evgueni N. Smirnov, A. M. Kaptein:
Theoretical and Experimental Study of a Meta-Typicalness Approach for Reliable Classification. ICDM Workshops 2006: 739-743 - [c12]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 - 2005
- [c11]Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, Georgi I. Nalbantov:
Reliable Instance Classification with Version Spaces. SGAI Conf. 2005: 288-301 - 2002
- [c10]Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, H. Jaap van den Herik:
Efficient Instance Retraction. AIMSA 2002: 21-30 - [c9]Evgueni N. Smirnov, H. Jaap van den Herik, Ida G. Sprinkhuizen-Kuyper:
Adaptable Boundary Sets. AI&M 2002 - [c8]Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, H. Jaap van den Herik:
New Version-Space Representations for Efficient Instance Retraction. KDID 2002: 32-49 - 2000
- [c7]Evgueni N. Smirnov, H. Jaap van den Herik:
Applying Preference Biases to Conjunctive and Disjunctive Version Spaces. AIMSA 2000: 321-330 - 1998
- [c6]Evgueni N. Smirnov, Peter J. Braspenning:
Version Space Retraction with Instance-Based Boundary Sets. AIMSA 1998: 389-402 - [c5]Evgueni N. Smirnov, Peter J. Braspenning:
Version Space Learning with Instance-Based Boundary Sets. ECAI 1998: 460-464 - 1996
- [c4]Nikolay I. Nikolaev, Evgueni N. Smirnov:
Stochastically Guided Disjunctive Version Space Learning. ECAI 1996: 443-447 - 1995
- [c3]Nikolay I. Nikolaev, Evgueni N. Smirnov:
Analytical Learning Guided by Empirical Technology: An Approach to Integration (Extended Abstract). ECML 1995: 327-330 - [c2]Evgueni N. Smirnov, Nikolay I. Nikolaev:
Multiple Explanation-based Learning Guided by Space Fragmenting. SCAI 1995: 85-96 - 1992
- [c1]Evgueni N. Smirnov:
Space Fragmenting - A Method of Disjunctive Concept Acquisition. AIMSA 1992: 97-104
Parts in Books or Collections
- 2011
- [p2]Evgueni N. Smirnov, Matthijs Moed, Georgi I. Nalbantov, Ida G. Sprinkhuizen-Kuyper
:
Minimally-Sized Balanced Decomposition Schemes for Multi-class Classification. Ensembles in Machine Learning Applications 2011: 39-58 - 2004
- [p1]Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, H. Jaap van den Herik:
One-Sided Instance-Based Boundary Sets. Database Support for Data Mining Applications 2004: 270-288
Editorship
- 2020
- [e3]Alexander Gammerman, Vladimir Vovk, Zhiyuan Luo, Evgueni N. Smirnov, Giovanni Cherubin, Marco Christini:
Conformal and Probabilistic Prediction and Applications, COPA 2020, 9-11 September 2020, Virtual Event. Proceedings of Machine Learning Research 128, PMLR 2020 [contents] - 2019
- [e2]Alex Gammerman, Vladimir Vovk, Zhiyuan Luo, Evgueni N. Smirnov:
Conformal and Probabilistic Prediction and Applications, COPA 2019, 9-11 September 2019, Golden Sands, Bulgaria. Proceedings of Machine Learning Research 105, PMLR 2019 [contents] - 2018
- [e1]Alex Gammerman, Vladimir Vovk, Zhiyuan Luo, Evgueni N. Smirnov, Ralf L. M. Peeters:
7th Symposium on Conformal and Probabilistic Prediction and Applications, COPA 2018, 11-13 June 2018, Maastricht, The Netherlands. Proceedings of Machine Learning Research 91, PMLR 2018 [contents]
Coauthor Index
aka: Nikolay Y. Nikolaev
aka: Ralf Peeters
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-05-02 21:48 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint