Tome Eftimov



Journal articlesshow all

OPTION: OPTImization Algorithm Benchmarking ONtology, IEEE TECV (2023)
Towards understanding the importance of time-series features in automated algorithm performance prediction, ESWA (2023)
CafeteriaSA corpus: Scientific abstracts annotated across different food semantic resources, DATABASE (2022)
CafeteriaFCD corpus: Food consumption data annotated with regard to different food semantic resources, FOODS (2022)
Dietary, comorbidity, and geo-economic data fusion for explainable COVID-19 mortality prediction, ESWA (2022)
Missing value imputation in Food Composition Data with Denoising Autoencoders, J FOOD COMPOS ANAL (2022)
In-depth Insights into Alzheimer’s Disease by using Explainable Machine Learning Approach, SCI REP-UK (2022)
Responsible Governance for a Food and Nutrition E-Infrastructure: Case Study of the Determinants and Intake Data Platform, FRONT NUTR (2022)
Transfer Learning Analysis of Multi-Class Classification for Landscape-Aware Algorithm Selection, MATHEMATICS (2022)
Less is more: Selecting the right benchmarking set of data for time series classification, EXPERT SYST APPL (2022)
Data-driven Intelligence System for General Recommendations of Deep Learning Architectures, IEEE ACCESS (2021)
Domain Heuristic Fusion of Multi-word Embeddings for Nutrient Value Prediction, MATHEMATICS (2021)
Designing a research infrastructure (RI) on food behaviour and health: Balancing user needs, business model, governance mechanisms and technology, TRENDS FOOD SCI TECH (2021)
A Fine-Tuned Bidirectional Encoder Representations From Transformers for Food Named-Entity Recognition: Algorithm Development and Validation, JMIR (2021)
Impact of COVID-19 confinement on eating behaviours across 16 European countries: the COVIDiet cross-national study, FOOD QUAL PREFER (2021)
A Framework for Evaluating Personalized Ranking Systems by Fusing Different Evaluation Measures, BIG DATA RES (2021)
Deep Statistical Comparison for Multi-objective Stochastic Optimization Algorithms, SWARM EVOL COMPUT (2021)

 

Conference papersshow all

Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms, EvoApps 2023
RF+clust for Leave-One-Problem-Out Performance Prediction, EvoApps 2023
Explainable Model-specific Algorithm Selection for Multi-Label Classification, IEEE SSCI 2022
TLA: Topological Landscape Analysis for Single-Objective Continuous Optimization Problem Instances, IEEE SSCI 2022
Explaining Differential Evolution Performance Through Problem Landscape Characteristics, BIOMA2022
Improving Nevergrad’s Algorithm Selection Wizard NGOpt Through Automated Algorithm Configuration, PPSN 2022
Per-Run Algorithm Selection with Warm-starting Using Trajectory-based Features, PPSN 2022
Identifying minimal set of Exploratory Landscape Analysis features for reliable algorithm performance prediction, IEEE CEC at IEEE WCCI 2022
Trajectory-based Algorithm Selection with Warm-starting, IEEE CEC at IEEE WCCI 2022
A Comprehensive Analysis of the Invariance of Exploratory Landscape Analysis Features to Function Transformations, IEEE CEC at IEEE WCCI 2022
The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants, GECCO 2022
SELECTOR: Selecting a Representative Benchmark Suite for Reproducible Statistical Comparison, GECCO 2022
Explainable Landscape Analysis in Automated Algorithm Performance Prediction, EvoAPPS 2022
Multimodal Analysis of User-Recipes Interactions, HEALTHINF 2022
FoodChem: A food-chemical relation extraction model, IEEE SSCI 2021
Explainable Landscape-Aware Optimization Performance Prediction, IEEE SSCI 2021
Robust Benchmarking for Multi-Objective Optimization, GECCO 2021
The Effect of Sampling Methods on the Invariance to Function Transforms when using Exploratory Landscape Analysis, IEEE CEC 2021
Reducing Bias in Multi-Objective Optimization Benchmarking, HOP at GECCO 2021
SAFFRON: tranSfer leArning For Food-Disease RelatiOn extractioN, BioNLP @ NAACL 2021
OPTION: OPTmization Algorithm Benchmarking ONtology, GECCO 2021
A Complementarity Analysis of the COCO Benchmark Problems and Artificially Generated Problems, GECCO 2021
The Impact of Hyper-Parameter Tuning for Landscape-Aware Performance Regression and Algorithm Selection, GECCO 2021
Personalizing Performance Regression Models to Black-Box Optimization Problems, GECCO 2021
Towards Feature-Based Performance Regression Using Trajectory Data, EvoAPPS-EvoStar 2021
Finding Potential Inhibitors of COVID-19, BIOINFORMATICS 2021
On Statistical Analysis of MOEAs with Multiple Performance Indicators, EMO2021

 

Books & Chaptersshow all

Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms, Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms, Springer Cham (2022)
Food Data Normalization Using Lexical and Semantic Similarities Heuristics, Biomedical Engineering Systems and Technologies. BIOSTEC 2020. Communications in Computer and Information Science, vol 1400. Springer, Cham., (2021)

 

Other publicationsshow all

Importance of Complete Food Composition Databases and Computer Methods for dealing with Missing Food Composition Data (2019)
Quality Improvement of Food Composition Databases Using Methods from Natural Language Processing and Statistics (2019)
Statistical data analysis and natural language processing for nutrition science (2018)
How to Perform a Proper Statistical Study Analysis? Where we Started and Where are we Now in Statistical Performance Assessment Approaches for Stochastic Optimization Algorithms? (2018)
Computer-supported borrowing of missing nutrient values in food composition databases (2018)
Differentiation of slovenian milk based on the content and carbon isotope composition of fatty acids (2017)
Mixed deep learning and natural language processing approach for food image detection, recognition and analysis to estimate nutritional values (2017)
Matching foods from EuroFIR databases to FoodEx by using a semi-automatic system for classifying and describing foods (2017)