Tome Eftimov



Journal articlesshow all

TinyTLA: Topological landscape analysis for optimization problem classification in a limited sample setting, SWARM EVOL COMPUT (2024)
MsGEN: Measuring Generalization of Nutrient Value Prediction across Different Recipe Datasets, ESWA (2024)
FooDis: A food-disease relation mining pipeline, Artificial intelligence in Medicine (2023)
From Language Models to Large-scale Food and Biomedical Knowledge Graphs, SCI REP-UK (2023)
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)

 

Conference papersshow all

Analyzing the Generalizability of Automated Algorithm Selection: A Case Study for Numerical Optimization, IEEE SSCI 2023
Enhancing Food Composition Databases: Predicting Missing Values via Knowledge Graph Embeddings, SIKDD
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization, AutoML 2023
Sensitivity Analysis of RF+clust for Leave-one-problem-out Performance Prediction, IEEE CEC 2023
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems, GECCO 2023
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems, GECCO 2023
Assessing the Generalizability of a Performance Predictive Model, GECCO 2023
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances, GECCO 2023
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

 

Books & Chaptersshow all

Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms, Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms, Springer Cham (2022)

 

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)