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ORCIDTome Eftimov
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- affiliation: Jozef Stefan Institute, Ljubljana, Slovenia
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2020 – today
- 2024
[j25]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)- [j24]Peter Korosec, Tome Eftimov:
Opt2Vec - a continuous optimization problem representation based on the algorithm's behavior: A case study on problem classification. Inf. Sci. 680: 121134 (2024) - [j23]Gasper Petelin, Gjorgjina Cenikj, Tome Eftimov:
TinyTLA: Topological landscape analysis for optimization problem classification in a limited sample setting. Swarm Evol. Comput. 84: 101448 (2024) - [j22]Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov:
A cross-benchmark examination of feature-based algorithm selector generalization in single-objective numerical optimization. Swarm Evol. Comput. 87: 101534 (2024) - [c95]Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov:
Impact of Scaling in ELA Feature Calculation on Algorithm Selection Cross-Benchmark Transferability. CEC 2024: 1-8 - [c94]Ana Nikolikj, Ana Kostovska, Gjorgjina Cenikj, Carola Doerr, Tome Eftimov:
Generalization Ability of Feature-Based Performance Prediction Models: A Statistical Analysis Across Benchmarks. CEC 2024: 1-8 - [c93]Ana Nikolikj, Ana Kostovska, Diederick Vermetten, Carola Doerr, Tome Eftimov:
Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks. CEC 2024: 1-8 - [c92]Ana Nikolikj, Tome Eftimov:
Comparing Solvability Patterns of Algorithms across Diverse Problem Landscapes. GECCO Companion 2024: 143-146 - [c91]Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov:
TransOptAS: Transformer-Based Algorithm Selection for Single-Objective Optimization. GECCO Companion 2024: 403-406 - [c90]Carolin Benjamins, Gjorgjina Cenikj, Ana Nikolikj, Aditya Mohan, Tome Eftimov, Marius Lindauer:
Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization. GECCO Companion 2024: 563-566 - [c89]Peter Korosec, Tome Eftimov:
Per-Run Algorithm Performance Improvement Forecasting Using Exploratory Landscape Analysis Features: A Case Study in Single-Objective Black-Box Optimization. GECCO Companion 2024: 571-574 - [c88]Tome Eftimov, Peter Korosec:
Statistical Analyses for Single-objective Stochastic Optimization Algorithms. GECCO Companion 2024: 1313-1327 - [c87]Marko Djukanovic, Aleksandar Kartelj, Tome Eftimov, Jaume Reixach, Christian Blum:
Efficient Search Algorithms for the Restricted Longest Common Subsequence Problem. ICCS (5) 2024: 58-73 - [i37]Ana Nikolikj, Ana Kostovska, Diederick Vermetten, Carola Doerr, Tome Eftimov:
Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks. CoRR abs/2405.11964 (2024) - [i36]Ana Nikolikj, Ana Kostovska, Gjorgjina Cenikj, Carola Doerr, Tome Eftimov:
Generalization Ability of Feature-based Performance Prediction Models: A Statistical Analysis across Benchmarks. CoRR abs/2405.12259 (2024) - [i35]Gjorgjina Cenikj, Ana Nikolikj, Gasper Petelin, Niki van Stein, Carola Doerr, Tome Eftimov:
A Survey of Meta-features Used for Automated Selection of Algorithms for Black-box Single-objective Continuous Optimization. CoRR abs/2406.06629 (2024) - [i34]Carolin Benjamins, Gjorgjina Cenikj, Ana Nikolikj, Aditya Mohan, Tome Eftimov, Marius Lindauer:
Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization. CoRR abs/2407.13513 (2024) - [i33]Marko Djukanovic, Jaume Reixach, Ana Nikolikj, Tome Eftimov, Aleksandar Kartelj, Christian Blum:
A Learning Search Algorithm for the Restricted Longest Common Subsequence Problem. CoRR abs/2410.12031 (2024) - 2023
- [j21]Gjorgjina Cenikj, Tome Eftimov, Barbara Korousic-Seljak:
FooDis: A food-disease relation mining pipeline. Artif. Intell. Medicine 142: 102586 (2023) - [j20]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) - [j19]Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: OPTImization Algorithm Benchmarking ONtology. IEEE Trans. Evol. Comput. 27(6): 1618-1632 (2023) - [c86]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. AutoML 2023: 11/1-17 - [c85]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 - [c84]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 - [c83]Ana Nikolikj, Carola Doerr, Tome Eftimov:
RF+clust for Leave-One-Problem-Out Performance Prediction. EvoApplications@EvoStar 2023: 285-301 - [c82]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 - [c81]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 - [c80]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 - [c79]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 - [c78]Urban Skvorc, Tome Eftimov, Peter Korosec:
Analyzing the Generalizability of Automated Algorithm Selection: A Case Study for Numerical Optimization. SSCI 2023: 335-340 - [i32]Ana Nikolikj, Carola Doerr, Tome Eftimov:
RF+clust for Leave-One-Problem-Out Performance Prediction. CoRR abs/2301.09524 (2023) - [i31]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) - [i30]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) - [i29]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) - [i28]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) - [i27]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) - [i26]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) - [i25]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) - [i24]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) - [i23]Gjorgjina Cenikj, Gasper Petelin, Tome Eftimov:
TransOpt: Transformer-based Representation Learning for Optimization Problem Classification. CoRR abs/2311.18035 (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] - [d2]Anja Jankovic, Ana Kostovska, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr:
Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data. Zenodo, 2022
- [d1]Ana Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov:
Linking Problem Landscape Features with the Performance of Individual CMA-ES Modules - Data. Zenodo, 2022 - [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]