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ORCIDOleg Lesota
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2020 – today
- 2024
[c13]Oleg Lesota
, Jonas Geiger, Max Walder, Dominik Kowald, Markus Schedl:
Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems. RecSys 2024: 1022-1027- [i10]Santa Pile, Oleg Lesota, Silvan David Peter, Christina Humer, Martin Gasser:
Spin-Wave Voices: Sonification of Nanoscale Spin Waves as an Engagement and Research Tool. CoRR abs/2405.03506 (2024) - [i9]Oleg Lesota, Jonas Geiger, Max Walder, Dominik Kowald, Markus Schedl:
Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems. CoRR abs/2408.11565 (2024) - [i8]Markus Schedl, Oleg Lesota, Stefan Brandl, Mohammad Lotfi, Gustavo Junior Escobedo Ticona, Shahed Masoudian:
The Importance of Cognitive Biases in the Recommendation Ecosystem. CoRR abs/2408.12492 (2024) - 2023
- [j2]Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Fritzl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl:
Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation. Int. J. Multim. Inf. Retr. 12(1): 13 (2023) - [c12]Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz:
Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results. CHIIR 2023: 444-448 - [c11]Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz:
Parameter-efficient Modularised Bias Mitigation via AdapterFusion. EACL 2023: 2730-2743 - [c10]Oleg Lesota, Gustavo Escobedo, Yashar Deldjoo, Bruce Ferwerda, Simone Kopeinik, Elisabeth Lex, Navid Rekabsaz, Markus Schedl:
Computational Versus Perceived Popularity Miscalibration in Recommender Systems. SIGIR 2023: 1889-1893 - [i7]Deepak Kumar, Oleg Lesota, George Zerveas, Daniel Cohen, Carsten Eickhoff, Markus Schedl, Navid Rekabsaz:
Parameter-efficient Modularised Bias Mitigation via AdapterFusion. CoRR abs/2302.06321 (2023) - 2022
- [c9]Markus Schedl, Stefan Brandl, Oleg Lesota, Emilia Parada-Cabaleiro, David Penz, Navid Rekabsaz:
LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis. CHIIR 2022: 337-341 - [c8]Oleg Lesota, Emilia Parada-Cabaleiro, Stefan Brandl, Elisabeth Lex, Navid Rekabsaz, Markus Schedl:
Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms. ISMIR 2022: 291-297 - [c7]Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Friztl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl:
EmoMTB: Emotion-aware Music Tower Blocks. ICMR 2022: 206-210 - [c6]Oleg Lesota, Stefan Brandl, Matthias Wenzel, Alessandro B. Melchiorre, Elisabeth Lex, Navid Rekabsaz, Markus Schedl:
Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization. MORS@RecSys 2022 - [c5]Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl:
Unlearning Protected User Attributes in Recommendations with Adversarial Training. SIGIR 2022: 2142-2147 - [i6]Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz:
Grep-BiasIR: A Dataset for Investigating Gender Representation-Bias in Information Retrieval Results. CoRR abs/2201.07754 (2022) - [i5]Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, Markus Schedl:
Unlearning Protected User Attributes in Recommendations with Adversarial Training. CoRR abs/2206.04500 (2022) - 2021
- [j1]Alessandro B. Melchiorre, Navid Rekabsaz, Emilia Parada-Cabaleiro, Stefan Brandl, Oleg Lesota, Markus Schedl:
Investigating gender fairness of recommendation algorithms in the music domain. Inf. Process. Manag. 58(5): 102666 (2021) - [c4]Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl:
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models. ICTIR 2021: 185-195 - [c3]Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? RecSys 2021: 601-606 - [c2]Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff:
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models. SIGIR 2021: 654-664 - [c1]Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff:
TripClick: The Log Files of a Large Health Web Search Engine. SIGIR 2021: 2507-2513 - [i4]Navid Rekabsaz, Oleg Lesota, Markus Schedl, Jon Brassey, Carsten Eickhoff:
TripClick: The Log Files of a Large Health Web Search Engine. CoRR abs/2103.07901 (2021) - [i3]Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff:
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models. CoRR abs/2105.04651 (2021) - [i2]Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl:
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models. CoRR abs/2106.13618 (2021) - [i1]Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? CoRR abs/2108.06973 (2021)
Coauthor Index
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