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ORCIDBernard Zenko
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2020 – today
- 2021
[j8]Zdravko Kunic
, Bernard Zenko, Biljana Mileva-Boshkoska:
FOCUSED-Short-Term Wind Speed Forecast Correction Algorithm Based on Successive NWP Forecasts for Use in Traffic Control Decision Support Systems. Sensors 21(10): 3405 (2021)- [c18]Martin Znidarsic, Aljaz Osojnik, Peter Rupnik, Bernard Zenko:
Improving Effectiveness of a Coaching System Through Preference Learning. PETRA 2021: 459-465
2010 – 2019
- 2019
- [c17]Martin Znidarsic, Bernard Zenko, Aljaz Osojnik, Marko Bohanec, Pance Panov, Helena Burger, Zlatko Matjacic, Mojca Debeljak:
Multi-criteria Modelling Approach for Ambient Assisted Coaching of Senior Adults. KEOD 2019: 87-93 - [c16]Yordan Dimitrov, Zlatka Gospodinova, Richard Wheeler, Martin Znidarsic, Bernard Zenko, Vera Veleva, Nadejda Miteva:
Social activity modelling and multimodal coaching for active aging. PETRA 2019: 608-615 - [i4]Marc G. Leguia, Zoran Levnajic, Ljupco Todorovski, Bernard Zenko:
Reconstructing dynamical networks via feature ranking. CoRR abs/1902.03896 (2019) - 2018
- [c15]Jihed Khiari, Luís Moreira-Matias, Ammar Shaker, Bernard Zenko, Saso Dzeroski:
MetaBags: Bagged Meta-Decision Trees for Regression. ECML/PKDD (1) 2018: 637-652 - [i3]Jihed Khiari, Luís Moreira-Matias, Ammar Shaker, Bernard Zenko, Saso Dzeroski:
MetaBags: Bagged Meta-Decision Trees for Regression. CoRR abs/1804.06207 (2018) - [i2]Matej Petkovic, Redouane Boumghar, Martin Breskvar, Saso Dzeroski, Dragi Kocev, Jurica Levatic, Luke Lucas, Aljaz Osojnik, Bernard Zenko, Nikola Simidjievski:
Machine learning for predicting thermal power consumption of the Mars Express Spacecraft. CoRR abs/1809.00542 (2018) - 2017
- [j7]Tea Tusar, Klemen Gantar, Valentin Koblar, Bernard Zenko, Bogdan Filipic:
A study of overfitting in optimization of a manufacturing quality control procedure. Appl. Soft Comput. 59: 77-87 (2017) - [i1]Nikola Simidjievski, Jovan Tanevski, Bernard Zenko, Zoran Levnajic, Ljupco Todorovski, Saso Dzeroski:
Decoupling approximation robustly reconstructs directed dynamical networks. CoRR abs/1712.03100 (2017) - 2016
- [j6]Dragan Gamberger, Bernard Zenko, Alexis Mitelpunkt, Netta Shachar, Nada Lavrac:
Clusters of male and female Alzheimer's disease patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Brain Informatics 3(3): 169-179 (2016) - 2015
- [c14]Dragan Gamberger, Bernard Zenko, Alexis Mitelpunkt, Nada Lavrac:
Identification of Gender Specific Biomarkers for Alzheimer's Disease. BIH 2015: 57-66 - [c13]Darko Zelenika, Janez Povh, Bernard Zenko:
Text Detection in Document Images by Machine Learning Algorithms. CORES 2015: 169-179 - [c12]Dragan Gamberger, Bernard Zenko, Alexis Mitelpunkt, Nada Lavrac:
Multilayer Clustering: Biomarker Driven Segmentation of Alzheimer's Disease Patient Population. IWBBIO (1) 2015: 134-145 - 2012
- [j5]Daniela Stojanova, Andrej Kobler, Peter Ogrinc, Bernard Zenko, Saso Dzeroski:
Estimating the risk of fire outbreaks in the natural environment. Data Min. Knowl. Discov. 24(2): 411-442 (2012) - [j4]Timo Aho, Bernard Zenko, Saso Dzeroski, Tapio Elomaa:
Multi-target regression with rule ensembles. J. Mach. Learn. Res. 13: 2367-2407 (2012) - 2011
- [c11]Marko Debeljak, Bernard Zenko, Ales Poljanec:
Predictive models of forest development in Slovenia. EnviroInfo 2011: 97-100 - [c10]Elena Ikonomovska, João Gama, Bernard Zenko, Saso Dzeroski:
Speeding-Up Hoeffding-Based Regression Trees With Options. ICML 2011: 537-544 - 2010
- [c9]Ivica Slavkov, Bernard Zenko, Saso Dzeroski:
Evaluation Method for Feature Rankings and their Aggregations for Biomarker Discovery. MLSB 2010: 122-135
2000 – 2009
- 2009
- [c8]Timo Aho, Bernard Zenko, Saso Dzeroski:
Rule Ensembles for Multi-target Regression. ICDM 2009: 21-30 - [r1]Saso Dzeroski, Pance Panov, Bernard Zenko:
Machine Learning, Ensemble Methods in. Encyclopedia of Complexity and Systems Science 2009: 5317-5325 - 2008
- [j3]Bernard Zenko:
Learning Predictive Clustering Rules. Informatica (Slovenia) 32(1): 95-96 (2008) - [c7]Bernard Zenko, Saso Dzeroski:
Learning Classification Rules for Multiple Target Attributes. PAKDD 2008: 454-465 - 2005
- [c6]Bernard Zenko, Saso Dzeroski, Jan Struyf:
Learning Predictive Clustering Rules. KDID 2005: 234-250 - 2004
- [j2]Saso Dzeroski, Bernard Zenko:
Is Combining Classifiers with Stacking Better than Selecting the Best One? Mach. Learn. 54(3): 255-273 (2004) - [j1]Saso Dzeroski, Bernard Zenko, Marko Debeljak:
A report on the fourth international workshop on environmental applications of machine learning (EAML 2004). SIGKDD Explor. 6(2): 155-156 (2004) - [c5]Bernard Zenko, Saso Dzeroski, Alfred B. Kobal, Darja Kobal Grum, Niko Arneri, Josko Osredkar, Milena Horvat:
Relating personality traits and mercury exposure in miners with machine learning methods. EnviroInfo (1) 2004: 400-412 - 2002
- [c4]Bernard Zenko, Saso Dzeroski:
Stacking with an Extended Set of Meta-level Attributes and MLR. ECML 2002: 493-504 - [c3]Saso Dzeroski, Bernard Zenko:
Is Combining Classifiers Better than Selecting the Best One. ICML 2002: 123-130 - [c2]Saso Dzeroski, Bernard Zenko:
Stacking with Multi-response Model Trees. Multiple Classifier Systems 2002: 201-211 - 2001
- [c1]Bernard Zenko, Ljupco Todorovski, Saso Dzeroski:
A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods. ICDM 2001: 669-670
Coauthor Index
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