Balázs Hidasi

40 papers A* 1A 13Journal 13Unranked 7

Year	Rank	Type	Title / Venue / Authors
2024	A	`conf`	Dynamic Product Image Generation and Recommendation at Scale for Personalized E-commerce. RecSys Ádám Tibor Czapp, Mátyás Jani, Bálint Domián, Balázs Hidasi
2024	J	`jnl`	Dynamic Product Image Generation and Recommendation at Scale for Personalized E-commerce. CoRR Ádám Tibor Czapp, Mátyás Jani, Bálint Domián, Balázs Hidasi
2023	A	`conf`	The Effect of Third Party Implementations on Reproducibility. RecSys Balázs Hidasi, Ádám Tibor Czapp
2023	J	`jnl`	The Effect of Third Party Implementations on Reproducibility. CoRR Balázs Hidasi, Ádám Tibor Czapp
2023	A	`conf`	Widespread Flaws in Offline Evaluation of Recommender Systems. RecSys Balázs Hidasi, Ádám Tibor Czapp
2023	J	`jnl`	Widespread Flaws in Offline Evaluation of Recommender Systems. CoRR Balázs Hidasi, Ádám Tibor Czapp
2022	—	`ch.`	Multimedia Recommender Systems: Algorithms and Challenges. Recommender Systems Handbook Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Yinwei Wei, Xiangnan He
2019	J	`jnl`	IEEE Access Special Section Editorial: Social Computing Applications for Smart Cities. IEEE Access Cristina Rottondi, Giacomo Verticale, Piero Fraternali, Jasminko Novak, Konstantinos Pelechrinis, Balázs Hidasi, Carmen Karina Vaca Ruiz
2018	—	`ch.`	Cutting-Edge Collaborative Recommendation Algorithms: Deep Learning. Collaborative Recommendations Balázs Hidasi
2018	A	`conf`	DLRS 2018: third workshop on deep learning for recommender systems. RecSys Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman
2018	A	`conf`	Multimedia recommender systems. RecSys Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Peter Knees
2018	—	`ed.`	Proceedings of the 3rd Workshop on Deep Learning for Recommender Systems, DLRS@RecSys 2018, Vancouver, BC, Canada, October 6, 2018 DLRS Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman
2018	A	`conf`	Recurrent Neural Networks with Top-k Gains for Session-based Recommendations. CIKM Balázs Hidasi, Alexandros Karatzoglou
2017	A	`conf`	DLRS 2017: Second Workshop on Deep Learning for Recommender Systems. RecSys Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Sander Dieleman, Bracha Shapira, Domonkos Tikk
2017	A	`conf`	Deep Learning for Recommender Systems. RecSys Alexandros Karatzoglou, Balázs Hidasi
2017	A	`conf`	Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. RecSys Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi
2017	J	`jnl`	Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. CoRR Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi
2017	—	`ed.`	Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, DLRS@RecSys 2017, Como, Italy, August 27, 2017 DLRS@RecSys Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Sander Dieleman, Bracha Shapira, Domonkos Tikk
2017	J	`jnl`	Recurrent Neural Networks with Top-k Gains for Session-based Recommendations. CoRR Balázs Hidasi, Alexandros Karatzoglou
2016	—	`—`	Context-aware factorization methods for implicit feedback based recommendation problems Balázs Hidasi
2016	J	`jnl`	General factorization framework for context-aware recommendations. Data Min. Knowl. Discov. Balázs Hidasi, Domonkos Tikk
2016	A	`conf`	Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations. RecSys Balázs Hidasi, Massimo Quadrana, Alexandros Karatzoglou, Domonkos Tikk
2016	—	`ed.`	Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, DLRS@RecSys 2016, Boston, MA, USA, September 15, 2016 DLRS@RecSys Alexandros Karatzoglou, Balázs Hidasi, Domonkos Tikk, Oren Sar Shalom, Haggai Roitman, Bracha Shapira, Lior Rokach
2016	A	`conf`	RecSys'16 Workshop on Deep Learning for Recommender Systems (DLRS). RecSys Alexandros Karatzoglou, Balázs Hidasi, Domonkos Tikk, Oren Sar Shalom, Haggai Roitman, Bracha Shapira, Lior Rokach
2016	A*	`conf`	Session-based Recommendations with Recurrent Neural Networks. ICLR (Poster) Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikk
2016	J	`jnl`	Speeding up ALS learning via approximate methods for context-aware recommendations. Knowl. Inf. Syst. Balázs Hidasi, Domonkos Tikk
2016	A	`conf`	The Contextual Turn: from Context-Aware to Context-Driven Recommender Systems. RecSys Roberto Pagano, Paolo Cremonesi, Martha A. Larson, Balázs Hidasi, Domonkos Tikk, Alexandros Karatzoglou, Massimo Quadrana
2016	J	`jnl`	Theano: A Python framework for fast computation of mathematical expressions. CoRR 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
2015	A	`conf`	Context-aware Preference Modeling with Factorization. RecSys Balázs Hidasi
2015	—	`conf`	Using Interaction Signals for Job Recommendations. MobiCASE Benjamin Kille, Fabian Abel, Balázs Hidasi, Sahin Albayrak
2014	—	`conf`	Approximate modeling of continuous context in factorization algorithms. CaRR@ECIR Balázs Hidasi, Domonkos Tikk
2014	J	`jnl`	General factorization framework for context-aware recommendations. CoRR Balázs Hidasi, Domonkos Tikk
2013	—	`conf`	Context-aware item-to-item recommendation within the factorization framework. CaRR@WSDM Balázs Hidasi, Domonkos Tikk
2013	J	`jnl`	Context-aware recommendations from implicit data via scalable tensor factorization. CoRR Balázs Hidasi, Domonkos Tikk
2013	J	`jnl`	Initializing Matrix Factorization Methods on Implicit Feedback Databases. J. Univers. Comput. Sci. Balázs Hidasi, Domonkos Tikk
2012	—	`conf`	Enhancing matrix factorization through initialization for implicit feedback databases. CaRR Balázs Hidasi, Domonkos Tikk
2012	—	`conf`	Fast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback. ECML/PKDD (2) Balázs Hidasi, Domonkos Tikk
2012	J	`jnl`	Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback CoRR Balázs Hidasi, Domonkos Tikk
2012	—	`conf`	Personalized recommendation of linear content on interactive TV platforms: beating the cold start and noisy implicit user feedback. UMAP Workshops Dávid Zibriczky, Balázs Hidasi, Zoltán Petres, Domonkos Tikk
2011	—	`conf`	ShiftTree: An Interpretable Model-Based Approach for Time Series Classification. ECML/PKDD (2) Balázs Hidasi, Csaba Gáspár-Papanek