Balázs Hidasi

According to our database, Balázs Hidasi authored at least 29 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Widespread Flaws in Offline Evaluation of Recommender Systems.

Balázs Hidasi, Ádám Tibor Czapp

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

The Effect of Third Party Implementations on Reproducibility.

Balázs Hidasi, Ádám Tibor Czapp

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

2022

Multimedia Recommender Systems: Algorithms and Challenges.

Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Yinwei Wei, Xiangnan He

Proceedings of the Recommender Systems Handbook, 2022

2019

IEEE Access Special Section Editorial: Social Computing Applications for Smart Cities.

Cristina Rottondi, Giacomo Verticale, Piero Fraternali, Jasminko Novak, Konstantinos Pelechrinis, Balázs Hidasi, Carmen Karina Vaca Ruiz

IEEE Access, 2019

2018

DLRS 2018: third workshop on deep learning for recommender systems.

Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Multimedia recommender systems.

Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Peter Knees

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Recurrent Neural Networks with Top-k Gains for Session-based Recommendations.

Balázs Hidasi, Alexandros Karatzoglou

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Cutting-Edge Collaborative Recommendation Algorithms: Deep Learning.

Balázs Hidasi

Proceedings of the Collaborative Recommendations, 2018

2017

Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks.

Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

Deep Learning for Recommender Systems.

Alexandros Karatzoglou, Balázs Hidasi

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

DLRS 2017: Second Workshop on Deep Learning for Recommender Systems.

Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Sander Dieleman, Bracha Shapira, Domonkos Tikk

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

2016

Context-aware factorization methods for implicit feedback based recommendation problems

Balázs Hidasi

PhD thesis, 2016

Speeding up ALS learning via approximate methods for context-aware recommendations.

Balázs Hidasi, Domonkos Tikk

Knowl. Inf. Syst., 2016

General factorization framework for context-aware recommendations.

Balázs Hidasi, Domonkos Tikk

Data Min. Knowl. Discov., 2016

Session-based Recommendations with Recurrent Neural Networks.

Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikk

Proceedings of the 4th International Conference on Learning Representations, 2016

Theano: A Python framework for fast computation of mathematical expressions.

Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

CoRR, 2016

The Contextual Turn: from Context-Aware to Context-Driven Recommender Systems.

Roberto Pagano, Paolo Cremonesi, Martha A. Larson, Balázs Hidasi, Domonkos Tikk, Alexandros Karatzoglou, Massimo Quadrana

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

RecSys'16 Workshop on Deep Learning for Recommender Systems (DLRS).

Alexandros Karatzoglou, Balázs Hidasi, Domonkos Tikk, Oren Sar Shalom, Haggai Roitman, Bracha Shapira, Lior Rokach

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations.

Balázs Hidasi, Massimo Quadrana, Alexandros Karatzoglou, Domonkos Tikk

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

2015

Context-aware Preference Modeling with Factorization.

Balázs Hidasi

Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Using Interaction Signals for Job Recommendations.

Benjamin Kille, Fabian Abel, Balázs Hidasi, Sahin Albayrak

Proceedings of the Mobile Computing, Applications, and Services, 2015

2014

Approximate modeling of continuous context in factorization algorithms.

Balázs Hidasi, Domonkos Tikk

Proceedings of the 4th Workshop on Context-Awareness in Retrieval and Recommendation, 2014

2013

Initializing Matrix Factorization Methods on Implicit Feedback Databases.

Balázs Hidasi, Domonkos Tikk

J. Univers. Comput. Sci., 2013

Context-aware recommendations from implicit data via scalable tensor factorization.

Balázs Hidasi, Domonkos Tikk

CoRR, 2013

Context-aware item-to-item recommendation within the factorization framework.

Balázs Hidasi, Domonkos Tikk

Proceedings of the 3rd Workshop on Context-awareness in Retrieval and Recommendation, 2013

2012

Personalized recommendation of linear content on interactive TV platforms: beating the cold start and noisy implicit user feedback.

Dávid Zibriczky, Balázs Hidasi, Zoltán Petres, Domonkos Tikk

Proceedings of the Workshop and Poster Proceedings of the 20th Conference on User Modeling, 2012

Fast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback.

Balázs Hidasi, Domonkos Tikk

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Enhancing matrix factorization through initialization for implicit feedback databases.

Balázs Hidasi, Domonkos Tikk

Proceedings of the 2nd Workshop on Context-awareness in Retrieval and Recommendation, 2012

2011

ShiftTree: An Interpretable Model-Based Approach for Time Series Classification.

Balázs Hidasi, Csaba Gáspár-Papanek

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011