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Publication search results
found 299 matches
- 2024
- Shahed Masoudian, Cornelia Volaucnik, Markus Schedl, Navid Rekabsaz:
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters. EACL (1) 2024: 2434-2453 - Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias. ECIR (4) 2024: 466-482 - Markus Schedl, Marta Moscati, Bruno Sguerra, Romain Hennequin, Elisabeth Lex:
Psychology-informed Information Access Systems Workshop. WSDM 2024: 1216-1217 - Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias. CoRR abs/2401.03883 (2024) - Shahed Masoudian, Cornelia Volaucnik, Markus Schedl, Navid Rekabsaz:
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters. CoRR abs/2401.16457 (2024) - 2023
- Markus Frohmann, Manuel Karner, Said Khudoyan, Robert Wagner, Markus Schedl:
Predicting the Price of Bitcoin Using Sentiment-Enriched Time Series Forecasting. Big Data Cogn. Comput. 7(3): 137 (2023) - 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) - Tommaso Di Noia, In-Young Ko, Markus Schedl:
Introduction to the ICWE 2022 Special Issue. J. Web Eng. 22(1): v-viii (2023) - Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
ReuseKNN: Neighborhood Reuse for Differentially Private KNN-Based Recommendations. ACM Trans. Intell. Syst. Technol. 14(5): 80:1-80:29 (2023) - Lukas Hauzenberger, Shahed Masoudian, Deepak Kumar, Markus Schedl, Navid Rekabsaz:
Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks. ACL (Findings) 2023: 6192-6214 - Dominik Kowald, Gregor Mayr, Markus Schedl, Elisabeth Lex:
A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations. BIAS 2023: 1-16 - Simone Kopeinik, Martina Mara, Linda Ratz, Klara Krieg, Markus Schedl, Navid Rekabsaz:
Show me a "Male Nurse"! How Gender Bias is Reflected in the Query Formulation of Search Engine Users. CHI 2023: 137:1-137:15 - Bruce Ferwerda, Eveline Ingesson, Michaela Berndl, Markus Schedl:
I Don't Care How Popular You Are! Investigating Popularity Bias in Music Recommendations from a User's Perspective. CHIIR 2023: 357-361 - 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 - 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 - Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz:
Domain Information Control at Inference Time for Acoustic Scene Classification. EUSIPCO 2023: 181-185 - Deepak Kumar, Tessa Grosz, Elisabeth Greif, Navid Rekabsaz, Markus Schedl:
Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning. HR@RecSys 2023 - Marta Moscati, Yashar Deldjoo, Giulio Davide Carparelli, Markus Schedl:
Multiobjective Hyperparameter Optimization of Recommender Systems. Perspectives@RecSys 2023 - Marta Moscati, Christian Wallmann, Markus Reiter-Haas, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation. RecSys 2023: 840-847 - Markus Schedl, Vito Walter Anelli, Elisabeth Lex:
Trustworthy Recommender Systems: Technical, Ethical, Legal, and Regulatory Perspectives. RecSys 2023: 1288-1290 - 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 - Veronika Arefieva, Roman Egger, Michael Schrefl, Markus Schedl:
Travel Bird: A Personalized Destination Recommender with TourBERT and Airbnb Experiences. WSDM 2023: 1164-1167 - Markus Schedl, Emilia Gómez, Elisabeth Lex:
Trustworthy Algorithmic Ranking Systems. WSDM 2023: 1240-1243 - 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) - Dominik Kowald, Gregor Mayr, Markus Schedl, Elisabeth Lex:
A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations. CoRR abs/2303.00400 (2023) - Shahed Masoudian, Khaled Koutini, Markus Schedl, Gerhard Widmer, Navid Rekabsaz:
Domain Information Control at Inference Time for Acoustic Scene Classification. CoRR abs/2306.08010 (2023) - 2022
- Darius Afchar, Alessandro B. Melchiorre, Markus Schedl, Romain Hennequin, Elena V. Epure, Manuel Moussallam:
Explainability in Music Recommender Systems. AI Mag. 43(2): 190-208 (2022) - Tommaso Di Noia, Nava Tintarev, Panagiota Fatourou, Markus Schedl:
Recommender systems under European AI regulations. Commun. ACM 65(4): 69-73 (2022) - Mihai Gabriel Constantin, Liviu-Daniel Stefan, Bogdan Ionescu, Claire-Hélène Demarty, Mats Sjöberg, Markus Schedl, Guillaume Gravier:
Affect in Multimedia: Benchmarking Violent Scenes Detection. IEEE Trans. Affect. Comput. 13(1): 347-366 (2022) - Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz:
Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements? BIAS 2022: 104-116
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