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ORCIDTome Eftimov
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- affiliation: Jozef Stefan Institute, Ljubljana, Slovenia
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2020 – today
- 2024
[j21]Gordana Ispirova, Tome Eftimov, Saso Dzeroski, Barbara Korousic-Seljak:
MsGEN: Measuring generalization of nutrient value prediction across different recipe datasets. Expert Syst. Appl. 237(Part B): 121507 (2024)- 2023
- [j20]Gjorgjina Cenikj
, Tome Eftimov, Barbara Korousic-Seljak:
FooDis: A food-disease relation mining pipeline. Artif. Intell. Medicine 142: 102586 (2023) - [j19]Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov:
Towards understanding the importance of time-series features in automated algorithm performance prediction. Expert Syst. Appl. 213(Part): 119023 (2023) - [c84]Ana Nikolikj, Michal Pluhacek, Carola Doerr, Peter Korosec, Tome Eftimov:
Sensitivity Analysis of RF+clust for Leave-One-Problem-Out Performance Prediction. CEC 2023: 1-8 - [c83]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Pance Panov, Tome Eftimov, Carola Doerr:
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms. EvoApplications@EvoStar 2023: 253-268 - [c82]Ana Nikolikj, Carola Doerr, Tome Eftimov:
RF+clust for Leave-One-Problem-Out Performance Prediction. EvoApplications@EvoStar 2023: 285-301 - [c81]Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
Assessing the Generalizability of a Performance Predictive Model. GECCO Companion 2023: 311-314 - [c80]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Saso Dzeroski, Tome Eftimov, Carola Doerr:
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems. GECCO Companion 2023: 495-498 - [c79]Ana Nikolikj, Saso Dzeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korosec, Tome Eftimov:
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances. GECCO 2023: 529-537 - [c78]Gjorgjina Cenikj, Gasper Petelin, Carola Doerr, Peter Korosec, Tome Eftimov:
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. GECCO 2023: 813-821 - [i31]Ana Nikolikj, Carola Doerr, Tome Eftimov:
RF+clust for Leave-One-Problem-Out Performance Prediction. CoRR abs/2301.09524 (2023) - [i30]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Pance Panov, Tome Eftimov, Carola Doerr:
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms. CoRR abs/2301.09876 (2023) - [i29]Gordana Ispirova, Tome Eftimov, Barbara Korousic-Seljak:
Predefined domain specific embeddings of food concepts and recipes: A case study on heterogeneous recipe datasets. CoRR abs/2302.01005 (2023) - [i28]Ana Nikolikj, Michal Pluhacek, Carola Doerr, Peter Korosec, Tome Eftimov:
Sensitivity Analysis of RF+clust for Leave-one-problem-out Performance Prediction. CoRR abs/2305.19375 (2023) - [i27]Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
Assessing the Generalizability of a Performance Predictive Model. CoRR abs/2306.00040 (2023) - [i26]Ana Nikolikj, Saso Dzeroski, Mario Andrés Muñoz, Carola Doerr, Peter Korosec, Tome Eftimov:
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances. CoRR abs/2306.00479 (2023) - [i25]Gjorgjina Cenikj, Gasper Petelin, Carola Doerr, Peter Korosec, Tome Eftimov:
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems. CoRR abs/2306.05438 (2023) - [i24]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Saso Dzeroski, Tome Eftimov, Carola Doerr:
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems. CoRR abs/2306.17585 (2023) - [i23]Ana Kostovska, Gjorgjina Cenikj, Diederick Vermetten, Anja Jankovic, Ana Nikolikj, Urban Skvorc, Peter Korosec, Carola Doerr, Tome Eftimov:
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization. CoRR abs/2310.10685 (2023) - 2022
- [b1]Tome Eftimov, Peter Korosec:
Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms. Natural Computing Series, Springer 2022, ISBN 978-3-030-96916-5, pp. 1-124 - [j18]Gjorgjina Cenikj, Eva Valencic, Gordana Ispirova, Matevz Ogrinc, Riste Stojanov, Peter Korosec, Ermanno Cavalli, Barbara Korousic-Seljak, Tome Eftimov:
CafeteriaSA corpus: scientific abstracts annotated across different food semantic resources. Database J. Biol. Databases Curation 2022(2022) (2022) - [j17]Tome Eftimov, Gasper Petelin, Gjorgjina Cenikj, Ana Kostovska, Gordana Ispirova, Peter Korosec, Jasmin Bogatinovski:
Less is more: Selecting the right benchmarking set of data for time series classification. Expert Syst. Appl. 198: 116871 (2022) - [j16]Milena Trajanoska, Risto Trajanov, Tome Eftimov:
Dietary, comorbidity, and geo-economic data fusion for explainable COVID-19 mortality prediction. Expert Syst. Appl. 209: 118377 (2022) - [j15]Christian Blum, Tome Eftimov, Peter Korosec:
Preface. Nat. Comput. 21(2): 127-130 (2022) - [c77]Gjorgjina Cenikj, Gasper Petelin, Barbara Korousic-Seljak, Tome Eftimov:
SciFoodNER: Food Named Entity Recognition for Scientific Text. IEEE Big Data 2022: 4065-4073 - [c76]Gordana Ispirova, Tome Eftimov, Barbara Korousic-Seljak:
Predefined domain specific embeddings of food concepts and recipes: A case study on heterogeneous recipe datasets. IEEE Big Data 2022: 4074-4083 - [c75]Ana Nikolikj, Ryan Dieter Lang, Peter Korosec, Tome Eftimov:
Explaining Differential Evolution Performance Through Problem Landscape Characteristics. BIOMA 2022: 99-113 - [c74]Emilija Georgievska, Martina Stojanoska, Sanja Mishovska, Tome Eftimov, Dimitar Trajanov:
Multimodal Analysis of User-recipes Interactions. HEALTHINF 2022: 689-696 - [c73]Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr:
Trajectory-based Algorithm Selection with Warm-starting. CEC 2022: 1-8 - [c72]Ana Nikolikj, Risto Trajanov, Gjorgjina Cenikj, Peter Korosec, Tome Eftimov:
Identifying minimal set of Exploratory Landscape Analysis features for reliable algorithm performance prediction. CEC 2022: 1-8 - [c71]Urban Skvorc, Tome Eftimov, Peter Korosec:
A Comprehensive Analysis of the Invariance of Exploratory Landscape Analysis Features to Function Transformations. CEC 2022: 1-8 - [c70]Risto Trajanov, Stefan Dimeski, Martin Popovski, Peter Korosec, Tome Eftimov:
Explainable Landscape Analysis in Automated Algorithm Performance Prediction. EvoApplications 2022: 207-222 - [c69]Gjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
SELECTOR: selecting a representative benchmark suite for reproducible statistical comparison. GECCO 2022: 620-629 - [c68]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov:
The importance of landscape features for performance prediction of modular CMA-ES variants. GECCO 2022: 648-656 - [c67]Tome Eftimov, Peter Korosec:
Statistical analyses for multi-objective stochastic optimization algorithms: GECCO 2022 tutorial. GECCO Companion 2022: 1342-1356 - [c66]Risto Trajanov, Ana Nikolikj, Gjorgjina Cenikj, Fabien Teytaud, Mathurin Videau, Olivier Teytaud, Tome Eftimov, Manuel López-Ibáñez, Carola Doerr:
Improving Nevergrad's Algorithm Selection Wizard NGOpt Through Automated Algorithm Configuration. PPSN (1) 2022: 18-31 - [c65]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr:
Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features. PPSN (1) 2022: 46-60 - [c64]Ana Kostovska, Carola Doerr, Saso Dzeroski, Dragi Kocev, Pance Panov, Tome Eftimov:
Explainable Model-specific Algorithm Selection for Multi-Label Classification. SSCI 2022: 39-46 - [c63]Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov:
TLA: Topological Landscape Analysis for Single-Objective Continuous Optimization Problem Instances. SSCI 2022: 1698-1705 - [e1]Marjan Mernik, Tome Eftimov, Matej Crepinsek:
Bioinspired Optimization Methods and Their Applications - 10th International Conference, BIOMA 2022, Maribor, Slovenia, November 17-18, 2022, Proceedings. Lecture Notes in Computer Science 13627, Springer 2022, ISBN 978-3-031-21093-8 [contents] - [i22]Risto Trajanov, Stefan Dimeski, Martin Popovski, Peter Korosec, Tome Eftimov:
Explainable Landscape Analysis in Automated Algorithm Performance Prediction. CoRR abs/2203.11828 (2022) - [i21]Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr:
Trajectory-based Algorithm Selection with Warm-starting. CoRR abs/2204.06397 (2022) - [i20]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov:
The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants. CoRR abs/2204.07431 (2022) - [i19]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr:
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features. CoRR abs/2204.09483 (2022) - [i18]Gjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
SELECTOR: Selecting a Representative Benchmark Suite for Reproducible Statistical Comparison. CoRR abs/2204.11527 (2022) - [i17]Risto Trajanov, Ana Nikolikj, Gjorgjina Cenikj, Fabien Teytaud, Mathurin Videau, Olivier Teytaud, Tome Eftimov, Manuel López-Ibáñez, Carola Doerr:
Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration. CoRR abs/2209.04412 (2022) - [i16]Ana Kostovska, Carola Doerr, Saso Dzeroski, Dragi Kocev, Pance Panov, Tome Eftimov:
Explainable Model-specific Algorithm Selection for Multi-Label Classification. CoRR abs/2211.11227 (2022) - [i15]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. CoRR abs/2211.11332 (2022) - 2021
- [j14]Gjorgji Noveski, Tome Eftimov, Kostadin Mishev, Monika Simjanoska:
Data-Driven Intelligence System for General Recommendations of Deep Learning Architectures. IEEE Access 9: 148710-148720 (2021) - [j13]Tome Eftimov, Bibek Paudel, Gorjan Popovski, Dragi Kocev:
A Framework for Evaluating Personalized Ranking Systems by Fusing Different Evaluation Measures. Big Data Res. 25: 100211 (2021) - [j12]Christian Blum, Tome Eftimov, Peter Korosec:
Preface. Nat. Comput. 20(3): 341-344 (2021) - [j11]Tome Eftimov, Peter Korosec:
Deep Statistical Comparison for Multi-Objective Stochastic Optimization Algorithms. Swarm Evol. Comput. 61: 100837 (2021) - [c62]Gjorgjina Cenikj, Bozhanka Vitanova, Tome Eftimov:
Skills Named-Entity Recognition for Creating a Skill Inventory of Today's Workplace. IEEE BigData 2021: 4561-4565 - [c61]Gjorgjina Cenikj, Tome Eftimov, Barbara Korousic-Seljak:
SAFFRON: tranSfer leArning For Food-disease RelatiOn extractioN. BioNLP@NAACL-HLT 2021: 30-40 - [c60]Angela Kralevska, Marija Velichkovska, Viktor Cicimov, Tome Eftimov, Monika Simjanoska:
Finding Potential Inhibitors of COVID-19. BIOINFORMATICS 2021: 110-117 - [c59]Urban Skvorc, Tome Eftimov, Peter Korosec:
The Effect of Sampling Methods on the Invariance to Function Transformations When Using Exploratory Landscape Analysis. CEC 2021: 1139-1146 - [c58]Hao Wang, Carlos Ignacio Hernández Castellanos, Tome Eftimov:
On Statistical Analysis of MOEAs with Multiple Performance Indicators. EMO 2021: 26-37 - [c57]Anja Jankovic, Tome Eftimov, Carola Doerr:
Towards Feature-Based Performance Regression Using Trajectory Data. EvoApplications 2021: 601-617 - [c56]Tome Eftimov, Peter Korosec:
Robust benchmarking for multi-objective optimization. GECCO Companion 2021: 9-10 - [c55]Tome Eftimov, Peter Korosec:
Reducing bias in multi-objective optimization benchmarking. GECCO Companion 2021: 27-28 - [c54]Urban Skvorc, Tome Eftimov, Peter Korosec:
A complementarity analysis of the COCO benchmark problems and artificially generated problems. GECCO Companion 2021: 215-216 - [c53]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: optimization algorithm benchmarking ontology. GECCO Companion 2021: 239-240 - [c52]Tome Eftimov, Anja Jankovic, Gorjan Popovski, Carola Doerr, Peter Korosec:
Personalizing performance regression models to black-box optimization problems. GECCO 2021: 669-677 - [c51]Anja Jankovic, Gorjan Popovski, Tome Eftimov, Carola Doerr:
The impact of hyper-parameter tuning for landscape-aware performance regression and algorithm selection. GECCO 2021: 687-696 - [c50]Tome Eftimov, Peter Korosec:
Statistical analyses for meta-heuristic stochastic optimization algorithms. GECCO Companion 2021: 770-785 - [c49]Gjorgjina Cenikj, Barbara Korousic-Seljak, Tome Eftimov:
FoodChem: A food-chemical relation extraction model. SSCI 2021: 1-8 - [c48]Risto Trajanov, Stefan Dimeski, Martin Popovski, Peter Korosec, Tome Eftimov:
Explainable Landscape-Aware Optimization Performance Prediction. SSCI 2021: 1-8 - [i14]Anja Jankovic, Tome Eftimov, Carola Doerr:
Towards Feature-Based Performance Regression Using Trajectory Data. CoRR abs/2102.05370 (2021) - [i13]Anja Jankovic, Gorjan Popovski, Tome Eftimov, Carola Doerr:
The Impact of Hyper-Parameter Tuning for Landscape-Aware Performance Regression and Algorithm Selection. CoRR abs/2104.09272 (2021) - [i12]Tome Eftimov, Anja Jankovic, Gorjan Popovski, Carola Doerr, Peter Korosec:
Personalizing Performance Regression Models to Black-Box Optimization Problems. CoRR abs/2104.10999 (2021) - [i11]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. CoRR abs/2104.11889 (2021) - [i10]Urban Skvorc, Tome Eftimov, Peter Korosec:
A Complementarity Analysis of the COCO Benchmark Problems and Artificially Generated Problems. CoRR abs/2104.13060 (2021) - [i9]Gjorgjina Cenikj, Barbara Korousic-Seljak, Tome Eftimov:
FoodChem: A food-chemical relation extraction model. CoRR abs/2110.02019 (2021) - [i8]Risto Trajanov, Stefan Dimeski, Martin Popovski, Peter Korosec, Tome Eftimov:
Explainable Landscape-Aware Optimization Performance Prediction. CoRR abs/2110.11633 (2021) - 2020
- [j10]Gorjan Popovski, Barbara Korousic-Seljak, Tome Eftimov:
A Survey of Named-Entity Recognition Methods for Food Information Extraction. IEEE Access 8: 31586-31594 (2020) - [j9]Tome Eftimov, Gasper Petelin, Peter Korosec:
DSCTool: A web-service-based framework for statistical comparison of stochastic optimization algorithms. Appl. Soft Comput. 87: 105977 (2020) - [j8]Urban Skvorc, Tome Eftimov, Peter Korosec:
Understanding the problem space in single-objective numerical optimization using exploratory landscape analysis. Appl. Soft Comput. 90: 106138 (2020) - [j7]Monika Simjanoska, Stefan Kochev, Jovan Tanevski, Ana Madevska Bogdanova, Gregor Papa, Tome Eftimov:
Multi-level information fusion for learning a blood pressure predictive model using sensor data. Inf. Fusion 58: 24-39 (2020) - [c47]Gjorgjina Cenikj, Gorjan Popovski, Riste Stojanov, Barbara Korousic-Seljak, Tome Eftimov:
BuTTER: BidirecTional LSTM for Food Named-Entity Recognition. IEEE BigData 2020: 3550-3556 - [c46]Bojan Dimoski, Riste Stojanov, Tome Eftimov, Hannah Pinchen, Maria Traka, Paul Finglas, Barbara Korousic-Seljak:
APRICOT: A humAn-comPuteR InteraCtion tool for linking foOd wasTe streams across different semantic resources. IEEE BigData 2020: 3557-3562 - [c45]Gordana Ispirova, Tome Eftimov, Barbara Korousic-Seljak:
Exploring Knowledge Domain Bias on a Prediction Task for Food and Nutrition Data. IEEE BigData 2020: 3563-3572 - [c44]Nina Resçiç, Tome Eftimov, Barbara Korousic-Seljak:
Comparison of Feature Selection Algorithms for Minimization of Target Specific FFQs. IEEE BigData 2020: 3592-3595 - [c43]Riste Stojanov, Ilija Kocev, Sasho Gramatikov, Gorjan Popovski, Barbara Korousic-Seljak, Tome Eftimov:
Toward Robust Food Ontology Mapping. IEEE BigData 2020: 3596-3601 - [c42]Gorjan Popovski, Gordana Ispirova, Nina Hadzi-Kotarova, Eva Valencic, Tome Eftimov, Barbara Korousic-Seljak:
Food Data Integration by using Heuristics based on Lexical and Semantic Similarities. HEALTHINF 2020: 208-216 - [c41]Stefan Kochev, Neven Stevchev, Svetlana Kocheva, Tome Eftimov, Monika Simjanoska:
A Novel Approach for Modelling the Relationship between Blood Pressure and ECG by using Time-series Feature Extraction. BIOSIGNALS 2020: 228-235 - [c40]Gordana Ispirova, Gorjan Popovski, Eva Valencic, Nina Hadzi-Kotarova, Tome Eftimov, Barbara Korousic-Seljak:
Food Data Normalization Using Lexical and Semantic Similarities Heuristics. BIOSTEC (Selected Papers) 2020: 468-485 - [c39]Tome Eftimov, Gasper Petelin, Rok Hribar, Gorjan Popovski, Urban Skvorc, Peter Korosec:
Deep statistics: more robust performance statistics for single-objective optimization benchmarking. GECCO Companion 2020: 5-6 - [c38]Tome Eftimov, Rok Hribar, Urban Skvorc, Gorjan Popovski, Gasper Petelin, Peter Korosec:
PerformViz: a machine learning approach to visualize and understand the performance of single-objective optimization algorithms. GECCO Companion 2020: 7-8 - [c37]Tome Eftimov, Peter Korosec:
Is the statistical significance between stochastic optimization algorithms' performances also significant in practice? GECCO Companion 2020: 19-20 - [c36]Urban Skvorc, Tome Eftimov, Peter Korosec:
Using exploratory landscape analysis to visualize single-objective problems. GECCO Companion 2020: 27-28 - [c35]Tome Eftimov, Gorjan Popovski, Dragi Kocev, Peter Korosec:
Performance2vec: a step further in explainable stochastic optimization algorithm performance. GECCO Companion 2020: 193-194 - [c34]Tome Eftimov, Peter Korosec:
Statistical analyses for meta-heuristic stochastic optimization algorithms: GECCO 2020 tutorial. GECCO Companion 2020: 724-746 - [c33]Gorjan Popovski, Gordana Ispirova, Eva Valencic, Riste Stojanov, Tome Eftimov, Barbara Korousic-Seljak:
An Insight into Food Semantics: Review, Analysis, and Lessons Learnt over Food-Related Studies (short paper). ICBO/ODLS 2020: 1-2 - [c32]Eva Tuba, Peter Korosec, Tome Eftimov:
In-Depth Insights into Swarm Intelligence Algorithms Performance. MDIS 2020: 334-346 - [c31]Riste Stojanov, Gorjan Popovski, Nasi Jofce, Dimitar Trajanov, Barbara Korousic-Seljak, Tome Eftimov:
FoodViz: Visualization of Food Entities Linked Across Different Standards. LOD (2) 2020: 28-38 - [c30]Tome Eftimov, Gorjan Popovski, Quentin Renau, Peter Korosec, Carola Doerr:
Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes. SSCI 2020: 775-782 - [i7]Thomas Bartz-Beielstein, Carola Doerr, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, Manuel López-Ibáñez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise:
Benchmarking in Optimization: Best Practice and Open Issues. CoRR abs/2007.03488 (2020) - [i6]Tome Eftimov, Gorjan Popovski, Quentin Renau, Peter Korosec, Carola Doerr:
Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes. CoRR abs/2009.14506 (2020) - [i5]Hao Wang, Carlos Ignacio Hernández Castellanos, Tome Eftimov:
On Statistical Analysis of MOEAs with Multiple Performance Indicators. CoRR abs/2012.00886 (2020)
2010 – 2019
- 2019
- [j6]Tome Eftimov, Peter Korosec:
Identifying practical significance through statistical comparison of meta-heuristic stochastic optimization algorithms. Appl. Soft Comput. 85 (2019) - [j5]Gorjan Popovski, Barbara Korousic-Seljak, Tome Eftimov:
FoodBase corpus: a new resource of annotated food entities. Database J. Biol. Databases Curation 2019: baz121 (2019) - [j4]Tome Eftimov, Peter Korosec:
A novel statistical approach for comparing meta-heuristic stochastic optimization algorithms according to the distribution of solutions in the search space. Inf. Sci. 489: 255-273 (2019) - [c29]Tome Eftimov, Dragi Kocev:
Performance Measures Fusion for Experimental Comparison of Methods for Multi-label Classification. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering 2019 - [c28]Bibek Paudel, Dragi Kocev, Tome Eftimov:
Mix and Rank: A Framework for Benchmarking Recommender Systems. IEEE BigData 2019: 3717-3726 - [c27]Martin Gjoreski, Stefan Kochev, Nina Resçiç, Matej Gregoric, Tome Eftimov, Barbara Korousic-Seljak:
Exploring Dietary Intake Data collected by FPQ using Unsupervised Learning. IEEE BigData 2019: 5126-5130 - [c26]Gordana Ispirova, Tome Eftimov, Barbara Korousic-Seljak:
Comparing Semantic and Nutrient Value Similarities of Recipes. IEEE BigData 2019: 5131-5139 - [c25]Gorjan Popovski, Bibek Paudel, Tome Eftimov, Barbara Korousic-Seljak:
Exploring a standardized language for describing foods using embedding techniques. IEEE BigData 2019: 5172-5176 - [c24]Riste Stojanov, Tome Eftimov, Hannah Pinchen, Maria Traka, Paul Finglas, Drago Torkar, Barbara Korousic-Seljak:
Food Waste Ontology: A Formal Description of Knowledge from the Domain of Food Waste. IEEE BigData 2019: 5190-5194 - [c23]Monika Simjanoska, Gregor Papa, Barbara Korousic-Seljak, Tome Eftimov:
Comparing Different Settings of Parameters Needed for Pre-processing of ECG Signals used for Blood Pressure Classification. BIOSIGNALS 2019: 62-72 - [c22]