Oleg Lesota

According to our database, Oleg Lesota authored at least 17 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

The Importance of Cognitive Biases in the Recommendation Ecosystem.

Markus Schedl, Oleg Lesota, Stefan Brandl, Mohammad Lotfi, Gustavo Junior Escobedo Ticona, Shahed Masoudian

CoRR, 2024

Spin-Wave Voices: Sonification of Nanoscale Spin Waves as an Engagement and Research Tool.

Santa Pile, Oleg Lesota, Silvan David Peter, Christina Humer, Martin Gasser

CoRR, 2024

Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems.

Oleg Lesota, Jonas Geiger, Max Walder, Dominik Kowald, Markus Schedl

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

2023

Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation.

Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Fritzl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl

Int. J. Multim. Inf. Retr., June, 2023

Computational Versus Perceived Popularity Miscalibration in Recommender Systems.

Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz, Markus Schedl

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Parameter-efficient Modularised Bias Mitigation via AdapterFusion.

Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results.

Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz

Proceedings of the 2023 Conference on Human Information Interaction and Retrieval, 2023

2022

Unlearning Protected User Attributes in Recommendations with Adversarial Training.

Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization.

Oleg Lesota, Stefan Brandl, Matthias Wenzel, Alessandro B. Melchiorre, Elisabeth Lex, Navid Rekabsaz, Markus Schedl

Proceedings of the 2nd Workshop on Multi-Objective Recommender Systems co-located with 16th ACM Conference on Recommender Systems (RecSys 2022), 2022

EmoMTB: Emotion-aware Music Tower Blocks.

Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Friztl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl

Proceedings of the ICMR '22: International Conference on Multimedia Retrieval, Newark, NJ, USA, June 27, 2022

Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms.

Oleg Lesota, Emilia Parada-Cabaleiro, Stefan Brandl, Elisabeth Lex, Navid Rekabsaz, Markus Schedl

Proceedings of the 23rd International Society for Music Information Retrieval Conference, 2022

LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis.

Markus Schedl, Stefan Brandl, Oleg Lesota, Emilia Parada-Cabaleiro, David Penz, Navid Rekabsaz

Proceedings of the CHIIR '22: ACM SIGIR Conference on Human Information Interaction and Retrieval, Regensburg, Germany, March 14, 2022

2021

Investigating gender fairness of recommendation algorithms in the music domain.

Alessandro B. Melchiorre, Navid Rekabsaz, Emilia Parada-Cabaleiro, Stefan Brandl, Oleg Lesota, Markus Schedl

Inf. Process. Manag., 2021

TripClick: The Log Files of a Large Health Web Search Engine.

Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models.

Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?

Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models.

Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl

Proceedings of the ICTIR '21: The 2021 ACM SIGIR International Conference on the Theory of Information Retrieval, 2021