publications

2023

  1. The Effect of Third Party Implementations on Reproducibility
    Balázs Hidasi, and Ádám Tibor Czapp
    In Proceedings of the 17th ACM Conference on Recommender Systems, 2023
    arXiv PDF Code Slides
  2. Widespread Flaws in Offline Evaluation of Recommender Systems
    Balázs Hidasi, and Ádám Tibor Czapp
    In Proceedings of the 17th ACM Conference on Recommender Systems, 2023
    arXiv PDF Code Poster

2022

  1. Multimedia Recommender Systems: Algorithms and Challenges
    Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Yinwei Wei, and Xiangnan He
    2022

2018

  1. Recurrent Neural Networks with Top-k Gains for Session-Based Recommendations
    Balázs Hidasi, and Alexandros Karatzoglou
    In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018
    arXiv PDF Code Slides
  2. DLRS 2018: Third Workshop on Deep Learning for Recommender Systems
    Balázs Hidasi, Alexandros Karatzoglou, Oren Sar-Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, and Sander Dieleman
    In Proceedings of the 12th ACM Conference on Recommender Systems, 2018
    PDF Website
  3. Multimedia Recommender Systems
    Yashar Deldjoo, Markus Schedl, Balázs Hidasi, and Peter Knees
    In Proceedings of the 12th ACM Conference on Recommender Systems, 2018
  4. Stimulating energy-saving behaviour through eco-feedback, adaptive gamification and personalized recommendations
    Jasminko Novak, Mark Melenhorst, Isabel Micheel, Piero Fraternali, Chiara Pasini, Sergio Herrera, and Balazs Hidasi
    In Proceedings of the 5th European Conference on Behaviour and Energy Efficiency(BEHAVE 2018), 2018
  5. Cutting-edge collaborative recommendation algorithms: Deep learning
    Balázs Hidasi
    In COLLABORATIVE RECOMMENDATIONS: Algorithms, Practical Challenges and Applications, 2018

2017

  1. Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks
    Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, and Paolo Cremonesi
    In Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017
    PDF
  2. DLRS 2017: Second Workshop on Deep Learning for Recommender Systems
    Balázs Hidasi, Alexandros Karatzoglou, Oren Sar-Shalom, Sander Dieleman, Bracha Shapira, and Domonkos Tikk
    In Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017
    PDF Website
  3. Deep Learning for Recommender Systems
    Alexandros Karatzoglou, and Balázs Hidasi
    In Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017
    PDF Slides

2016

  1. Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations
    Balázs Hidasi, Massimo Quadrana, Alexandros Karatzoglou, and Domonkos Tikk
    In Proceedings of the 10th ACM Conference on Recommender Systems, 2016
    PDF Slides
  2. RecSys’16 Workshop on Deep Learning for Recommender Systems (DLRS)
    Alexandros Karatzoglou, Balázs Hidasi, Domonkos Tikk, Oren Sar-Shalom, Haggai Roitman, and Bracha Shapira
    In Proceedings of the 10th ACM Conference on Recommender Systems, 2016
    PDF Website
  3. The Contextual Turn: From Context-Aware to Context-Driven Recommender Systems
    Roberto Pagano, Paolo Cremonesi, Martha Larson, Balázs Hidasi, Domonkos Tikk, Alexandros Karatzoglou, and Massimo Quadrana
    In Proceedings of the 10th ACM Conference on Recommender Systems, 2016
    PDF
  4. Session-based Recommendations with Recurrent Neural Networks
    Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk
    International Conference on Learning Representations, 2016
    arXiv PDF Code Poster
  5. General factorization framework for context-aware recommendations
    Balázs Hidasi, and Domonkos Tikk
    Data Mining and Knowledge Discovery, 2016
    First online: 07 May 2015
    PDF
  6. Speeding up ALS learning via approximate methods for context-aware recommendations
    Balázs Hidasi, and Domonkos Tikk
    Knowledge and Information Systems, 2016
    First online: 14 July 2015
    PDF
  7. Theano: A Python framework for fast computation of mathematical expressions
    The Theano Development Team, Balázs Hidasi, and  al.
    Technical Report, 2016
    arXiv
  8. Context-aware factorization algorithms for implicit feedback based recommendation problems
    Balázs Hidasi
    Ph.D. Thesis, 2016
    PDF Slides

2015

  1. Context-aware Preference Modeling with Factorization
    Balázs Hidasi
    In Proceedings of the 9th ACM Conference on Recommender Systems, 2015
    PDF Poster Slides
  2. Neighbor methods vs. matrix factorization—Case studies of real-life recommendations
    I Pilászy, A Serény, G Dózsa, B Hidasi, A Sári, and J Gub
    Proceedings of the ACM RecSys, 2015
  3. Mobile Computing, Applications, and Services: 7th International Conference, MobiCASE 2015, Berlin, Germany, November 12-13, 2015, Revised Selected Papers
    Benjamin Kille, Fabian Abel, Balázs Hidasi, and Sahin Albayrak
    2015
    PDF

2014

  1. Factorization models for context-aware recommendations
    Balázs Hidasi
    Infocommunications Journal, 2014
    PDF
  2. Approximate Modeling of Continuous Context in Factorization Algorithms
    Balázs Hidasi, and Domonkos Tikk
    In Proceedings of the 4th Workshop on Context-Awareness in Retrieval and Recommendation, 2014
    PDF Slides

2013

  1. Initializing Matrix Factorization Methods on Implicit Feedback Databases
    Balázs Hidasi, and Domonkos Tikk
    Journal of Universal Computer Science, Jun 2013
    PDF
  2. Context-aware Item-to-item Recommendation Within the Factorization Framework
    Balázs Hidasi, and Domonkos Tikk
    In Proceedings of the 3rd Workshop on Context-awareness in Retrieval and Recommendation, Jun 2013
    PDF Slides

2012

  1. Fast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback
    Balázs Hidasi, and Domonkos Tikk
    In Machine Learning and Knowledge Discovery in Databases, Jun 2012
    PDF Poster Slides
  2. Enhancing Matrix Factorization Through Initialization for Implicit Feedback Databases
    Balázs Hidasi, and Domonkos Tikk
    In Proceedings of the 2Nd Workshop on Context-awareness in Retrieval and Recommendation, Jun 2012
    PDF Slides
  3. Personalized recommendation of linear content on interactive TV platforms: beating the cold start and noisy implicit user feedback
    Dávid Zibriczky, Balázs Hidasi, Zoltán Petres, and Domonkos Tikk
    In UMAP Workshops. Proceedings of the International Workshop on TV and Multimedia Personalization, Jun 2012

2011

  1. ShiftTree: An Interpretable Model-Based Approach for Time Series Classification
    Balázs Hidasi, and Csaba Gáspár-Papanek
    In Machine Learning and Knowledge Discovery in Databases, Jun 2011
    PDF Poster Slides
  2. Modell alapú idősor-osztályozó fejlesztése és kiterjesztése
    Balázs Hidasi
    M.Sc. Thesis, Jun 2011
    PDF Slides

2009

  1. Újfajta, automatikus, döntési fa alapú adatbányászati módszer idősorok osztályozására (extended abstract)
    Balázs Hidasi
    In Proceedings of the 2009. évi Végzős Konferencia, Jun 2009
    PDF Slides

2008

  1. Újfajta, automatikus, döntési fa alapú adatbányászati módszer idősorok osztályozására
    Balázs Hidasi
    B.Sc. Thesis, Jun 2008
    PDF Slides
  2. Az idősor-osztályozás problémájának megoldása új, döntési fa alapú adatbányászati algoritmussal
    Balázs Hidasi
    Dissertation for the Students’ Scientific Conference, Jun 2008
    PDF Slides