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Ekhine Irurozki
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2020 – today
- 2024
- [j9]Mikel Malagon
, Ekhine Irurozki
A Combinatorial Optimization Framework for Probability-Based Algorithms by Means of Generative Models. ACM Trans. Evol. Learn. Optim. 4(3): 18:1-18:28 (2024) - [c15]Isaia Andrenacci, Matteo Lonardi, Petros Ramantanis, Elie Awwad, Ekhiñe Irurozki, Stéphan Clémençon, Paolo Serena, Chiara Lasagni, Sébastien Bigo, Patricia Layec:
Machine Learning-Driven Low-Complexity Optical Power Optimization for Point-to-Point Links. OFC 2024: 1-3 - 2023
- [j8]Yingqian Zhang
The first AI4TSP competition: Learning to solve stochastic routing problems. Artif. Intell. 319: 103918 (2023) - [j7]Etor Arza
Comparing Two Samples Through Stochastic Dominance: A Graphical Approach. J. Comput. Graph. Stat. 32(2): 551-566 (2023) - [c14]Morgane Goibert, Clément Calauzènes, Ekhine Irurozki, Stéphan Clémençon:
Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues. ICML 2023: 11584-11597 - [c13]Isaia Andrenacci, Matteo Lonardi, Petros Ramantanis, Elie Awwad, Ekhiñe Irurozki, Stéphan Clémençon:
Fast and accurate nonlinear interference in-band spectrum prediction for sparse channel allocation. ONDM 2023: 1-5 - [i10]Morgane Goibert, Clément Calauzènes, Ekhine Irurozki, Stéphan Clémençon:
Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues. CoRR abs/2303.12878 (2023) - [i9]Etor Arza, Josu Ceberio, Ekhiñe Irurozki, Aritz Pérez:
On the Fair Comparison of Optimization Algorithms in Different Machines. CoRR abs/2305.07345 (2023) - [i8]Anas Himmi, Ekhine Irurozki, Nathan Noiry, Stéphan Clémençon, Pierre Colombo:
Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks. CoRR abs/2305.10284 (2023) - 2022
- [c12]Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi:
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. AISTATS 2022: 10376-10406 - [c11]Etor Arza
Implementing the cumulative difference plot in the IOHanalyzer. GECCO Companion 2022: 11-12 - [c10]Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon:
What are the best Systems? New Perspectives on NLP Benchmarking. NeurIPS 2022 - [i7]Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi:
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. CoRR abs/2201.08105 (2022) - [i6]Laurens Bliek
The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems. CoRR abs/2201.10453 (2022) - [i5]Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon:
What are the best systems? New perspectives on NLP Benchmarking. CoRR abs/2202.03799 (2022) - [i4]Etor Arza, Josu Ceberio, Ekhiñe Irurozki, Aritz Pérez:
Comparing two samples through stochastic dominance: a graphical approach. CoRR abs/2203.07889 (2022) - 2021
- [c9]Ekhine Irurozki, Manuel López-Ibáñez:
Unbalanced mallows models for optimizing expensive black-box permutation problems. GECCO 2021: 225-233 - [c8]Fabien Collas, Ekhine Irurozki:
Concentric mixtures of Mallows models for top-k rankings: sampling and identifiability. ICML 2021: 2079-2088 - [c7]Ekhine Irurozki
Rank Aggregation for Non-stationary Data Streams. ECML/PKDD (3) 2021: 297-313 - 2020
- [j6]Etor Arza
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem. Swarm Evol. Comput. 59: 100740 (2020) - [c6]Mikel Malagon
Alternative Representations for Codifying Solutions in Permutation-Based Problems. CEC 2020: 1-8 - [c5]Etor Arza
An adaptive neuroevolution-based hyperheuristic. GECCO Companion 2020: 111-112 - [i3]Fabien Collas, Ekhine Irurozki:
Concentric mixtures of Mallows models for top-k rankings: sampling and identifiability. CoRR abs/2010.14260 (2020)
2010 – 2019
- 2019
- [c4]Etor Arza
Approaching the quadratic assignment problem with kernels of mallows models under the hamming distance. GECCO (Companion) 2019: 141-142 - [i2]Ekhine Irurozki, Jesus L. Lobo, Aritz Pérez, Javier Del Ser:
Online Ranking with Concept Drifts in Streaming Data. CoRR abs/1910.08795 (2019) - [i1]Etor Arza, Aritz Pérez, Ekhine Irurozki, Josu Ceberio:
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem. CoRR abs/1910.08800 (2019) - 2018
- [j5]Ekhine Irurozki
Algorithm 989: perm_mateda: A Matlab Toolbox of Estimation of Distribution Algorithms for Permutation-based Combinatorial Optimization Problems. ACM Trans. Math. Softw. 44(4): 47:1-47:13 (2018) - 2015
- [j4]Josu Ceberio
A review of distances for the Mallows and Generalized Mallows estimation of distribution algorithms. Comput. Optim. Appl. 62(2): 545-564 (2015) - 2014
- [j3]Josu Ceberio
A Distance-Based Ranking Model Estimation of Distribution Algorithm for the Flowshop Scheduling Problem. IEEE Trans. Evol. Comput. 18(2): 286-300 (2014) - [c3]Josu Ceberio
Extending distance-based ranking models in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2014: 2459-2466 - 2012
- [j2]Josu Ceberio
A review on estimation of distribution algorithms in permutation-based combinatorial optimization problems. Prog. Artif. Intell. 1(1): 103-117 (2012) - 2011
- [j1]Ekhine Irurozki
A Preprocessing Procedure for Haplotype Inference by Pure Parsimony. IEEE ACM Trans. Comput. Biol. Bioinform. 8(5): 1183-1195 (2011) - [c2]Ekhine Irurozki, Borja Calvo, José Antonio Lozano:
Learning Probability Distributions over Permutations by Means of Fourier Coefficients. Canadian AI 2011: 186-191
2000 – 2009
- 2009
- [c1]Ekhine Irurozki
A new preprocessing procedure for the haplotype inference problem. IEEE Congress on Evolutionary Computation 2009: 1320-1327
Coauthor Index
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