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Peter Müllner
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2020 – today
- 2024
- [j3]Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
Differential privacy in collaborative filtering recommender systems: a review. Frontiers Big Data 6 (2024) - [c6]Peter Müllner
, Elisabeth Lex
, Markus Schedl
, Dominik Kowald
:
The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias. ECIR (4) 2024: 466-482 - [i8]Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald:
The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias. CoRR abs/2401.03883 (2024) - [i7]Gustavo Escobedo, Marta Moscati, Peter Muellner, Simone Kopeinik, Dominik Kowald, Elisabeth Lex, Markus Schedl:
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models. CoRR abs/2406.11505 (2024) - [i6]Tomislav Duricic, Peter Müllner, Nicole Weidinger, Neven A. M. ElSayed, Dominik Kowald, Eduardo E. Veas:
AI-Powered Immersive Assistance for Interactive Task Execution in Industrial Environments. CoRR abs/2407.09147 (2024) - 2023
- [j2]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) - [c5]Peter Müllner
:
User Privacy in Recommender Systems. ECIR (3) 2023: 456-461 - 2022
- [c4]Peter Müllner, Stefan Schmerda, Dieter Theiler, Stefanie N. Lindstaedt, Dominik Kowald
:
Towards employing recommender systems for supporting data and algorithm sharing. DE@CoNEXT 2022: 8-14 - [c3]Markus Gansberger, Christian Fasching, Christoph Berndl, Martin Hirt, Peter Müllner, Franz Handler:
Innovation Farm - Innovative Technologien für die Landwirtschaft erlebbar machen. GIL Jahrestagung 2022: 319-322 - [i5]Peter Müllner, Markus Schedl, Elisabeth Lex, Dominik Kowald:
ReuseKNN: Neighborhood Reuse for Privacy-Aware Recommendations. CoRR abs/2206.11561 (2022) - [i4]Peter Müllner, Stefan Schmerda, Dieter Theiler, Stefanie N. Lindstaedt, Dominik Kowald:
Towards Employing Recommender Systems for Supporting Data and Algorithm Sharing. CoRR abs/2210.11828 (2022) - 2021
- [j1]Dominik Kowald
, Peter Müllner
, Eva Zangerle
, Christine Bauer
, Markus Schedl
, Elisabeth Lex
:
Support the underground: characteristics of beyond-mainstream music listeners. EPJ Data Sci. 10(1): 14 (2021) - [c2]Peter Müllner, Dominik Kowald
, Elisabeth Lex:
Robustness of Meta Matrix Factorization Against Strict Privacy Constraints. ECIR (2) 2021: 107-119 - [i3]Peter Müllner, Dominik Kowald, Elisabeth Lex:
Robustness of Meta Matrix Factorization Against Strict Privacy Constraints. CoRR abs/2101.06927 (2021) - [i2]Dominik Kowald, Peter Müllner, Eva Zangerle, Christine Bauer, Markus Schedl, Elisabeth Lex:
Support the Underground: Characteristics of Beyond-Mainstream Music Listeners. CoRR abs/2102.12188 (2021) - [i1]Peter Müllner, Elisabeth Lex, Dominik Kowald:
Position Paper on Simulating Privacy Dynamics in Recommender Systems. CoRR abs/2109.06473 (2021)
2010 – 2019
- 2012
- [c1]Adrian Rothenbuhler, Elisa H. Barney Smith
, Peter Müllner:
Application of image processing to track twin boundary motion in magnetic shape memory alloys. Image Processing: Machine Vision Applications 2012: 83000A
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