12 citations · 21 across the 8 of their papers we have counts for
3 papers · 1 filter
Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks
Anas Himmi, Ekhine Irurozki, Nathan Noiry +2
The evaluation of natural language processing (NLP) systems is crucial for advancing the field, but current benchmarking approaches often assume that all systems have scores availa…
On the Fair Comparison of Optimization Algorithms in Different Machines
Etor Arza, Josu Ceberio, Ekhiñe Irurozki +1
An experimental comparison of two or more optimization algorithms requires the same computational resources to be assigned to each algorithm. When a maximum runtime is set as the s…
Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues
Morgane Goibert, Clément Calauzènes, Ekhine Irurozki +1
As the issue of robustness in AI systems becomes vital, statistical learning techniques that are reliable even in presence of partly contaminated data have to be developed. Prefere…