Gjorgjina Cenikj

Orcid: 0000-0002-2723-0821

According to our database1, Gjorgjina Cenikj authored at least 20 papers between 2020 and 2024.

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Bibliography

2024
TinyTLA: Topological landscape analysis for optimization problem classification in a limited sample setting.
Swarm Evol. Comput., February, 2024

2023
FooDis: A food-disease relation mining pipeline.
Artif. Intell. Medicine, August, 2023

Towards understanding the importance of time-series features in automated algorithm performance prediction.
Expert Syst. Appl., 2023

TransOpt: Transformer-based Representation Learning for Optimization Problem Classification.
CoRR, 2023

How Far Out of Distribution Can We Go With ELA Features and Still Be Able to Rank Algorithms?
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Assessing the Generalizability of a Performance Predictive Model.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023

PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization.
Proceedings of the International Conference on Automated Machine Learning, 2023

2022
Less is more: Selecting the right benchmarking set of data for time series classification.
Expert Syst. Appl., 2022

CafeteriaSA corpus: scientific abstracts annotated across different food semantic resources.
Database J. Biol. Databases Curation, 2022

TLA: Topological Landscape Analysis for Single-Objective Continuous Optimization Problem Instances.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Improving Nevergrad's Algorithm Selection Wizard NGOpt Through Automated Algorithm Configuration.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

SELECTOR: selecting a representative benchmark suite for reproducible statistical comparison.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

Identifying minimal set of Exploratory Landscape Analysis features for reliable algorithm performance prediction.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022

SciFoodNER: Food Named Entity Recognition for Scientific Text.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
FoodChem: A food-chemical relation extraction model.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

SAFFRON: tranSfer leArning For Food-disease RelatiOn extractioN.
Proceedings of the 20th Workshop on Biomedical Language Processing, 2021

Skills Named-Entity Recognition for Creating a Skill Inventory of Today's Workplace.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Boosting Recommender Systems with Advanced Embedding Models.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

BuTTER: BidirecTional LSTM for Food Named-Entity Recognition.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020


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