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2020 – today
- 2023
[j3]Domokos M. Kelen, András A. Benczúr:
A probabilistic perspective on nearest neighbor for implicit recommendation. Int. J. Data Sci. Anal. 16(2): 217-235 (2023)- [c9]Domokos M. Kelen, Mihály Petreczky, Péter Kersch, András A. Benczúr:
Theoretical Evaluation of Asymmetric Shapley Values for Root-Cause Analysis. ICDM 2023: 210-219 - [i3]Ferenc Béres, István András Seres, Domokos M. Kelen, András A. Benczúr:
ethp2psim: Evaluating and deploying privacy-enhanced peer-to-peer routing protocols for the Ethereum network. CoRR abs/2306.15024 (2023) - [i2]Domokos M. Kelen, Mihály Petreczky, Péter Kersch, András A. Benczúr:
Theoretical Evaluation of Asymmetric Shapley Values for Root-Cause Analysis. CoRR abs/2310.09961 (2023) - 2022
- [c8]Domokos M. Kelen, Péter Kersch, András A. Benczúr:
Causal Explanations for Performance in Radio Networks. AI6G@WCCI 2022 - [i1]Domokos Miklós Kelen, István András Seres:
Towards Measuring The Fungibility and Anonymity of Cryptocurrencies. CoRR abs/2211.04259 (2022) - 2021
- [c7]András Benczúr, Ferenc Béres
, Domokos Kelen, Róbert Pálovics:
Tutorial on graph stream analytics. DEBS 2021: 168-171 - [c6]Domokos M. Kelen, András A. Benczúr:
A probabilistic perspective on nearest neighbor for implicit recommendation. ICDM (Workshops) 2021: 27-35
2010 – 2019
- 2019
- [j2]Ferenc Béres, Domokos M. Kelen, Róbert Pálovics, András A. Benczúr:
Node embeddings in dynamic graphs. Appl. Netw. Sci. 4(1): 64:1-64:25 (2019) - [j1]Domokos Kelen, Bálint Daróczy, Frederick Ayala-Gómez, Anna Ország, András Benczúr:
Session Recommendation via Recurrent Neural Networks over Fisher Embedding Vectors. Sensors 19(16): 3498 (2019) - [c5]Emily Sullivan, Dimitrios Bountouridis, Jaron Harambam, Shabnam Najafian, Felicia Loecherbach, Mykola Makhortykh, Domokos Kelen, Daricia Wilkinson, David Graus, Nava Tintarev:
Reading News with a Purpose: Explaining User Profiles for Self-Actualization. UMAP (Adjunct Publication) 2019: 241-245 - 2018
- [c4]Domokos M. Kelen, Dániel Berecz, Ferenc Béres, András A. Benczúr:
Efficient K-NN for Playlist Continuation. RecSys Challenge 2018: 6:1-6:4 - 2017
- [c3]Erzsébet Frigó, Róbert Pálovics, Domokos Kelen, Levente Kocsis, András A. Benczúr:
Alpenglow: Open Source Recommender Framework with Time-aware Learning and Evaluation. RecSys Posters 2017 - [c2]Erzsébet Frigó, Róbert Pálovics, Domokos Kelen, Levente Kocsis, András A. Benczúr:
Online Ranking Prediction in Non-stationary Environments. RecTemp@RecSys 2017: 28-34 - [c1]Róbert Pálovics, Domokos Kelen, András A. Benczúr:
Tutorial on Open Source Online Learning Recommenders. RecSys 2017: 400-401
Coauthor Index
aka: András Benczúr
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