| Techniques for dealing with incomplete data: a tutorial and survey M Aste, M Boninsegna, A Freno, E Trentin Pattern Analysis and Applications 18, 1-29, 2015 | 59 | 2015 |
| Practical lessons from developing a large-scale recommender system at Zalando A Freno Proceedings of the eleventh ACM conference on recommender systems, 251-259, 2017 | 33 | 2017 |
| Hybrid random fields A Freno, E Trentin Springer, 2011 | 23 | 2011 |
| Unsupervised nonparametric density estimation: A neural network approach E Trentin, A Freno 2009 International Joint Conference on Neural Networks, 3140-3147, 2009 | 18 | 2009 |
| Scalable pseudo-likelihood estimation in hybrid random fields A Freno, E Trentin, M Gori Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 16 | 2009 |
| One-pass ranking models for low-latency product recommendations A Freno, M Saveski, R Jenatton, C Archambeau Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 14 | 2015 |
| Learning to recommend links using graph structure and node content A Freno, GC Garriga, M Keller Neural information processing systems workshop on choice models and …, 2011 | 10 | 2011 |
| Kernel-based hybrid random fields for nonparametric density estimation A Freno, E Trentin, M Gori ECAI 2010, 427-432, 2010 | 8 | 2010 |
| Scalable statistical learning: A modular bayesian/markov network approach A Freno, E Trentin, M Gori 2009 International Joint Conference on Neural Networks, 890-897, 2009 | 8 | 2009 |
| Selecting features by learning markov blankets A Freno Knowledge-Based Intelligent Information and Engineering Systems: 11th …, 2007 | 8 | 2007 |
| Probabilistic interpretation of neural networks for the classification of vectors, sequences and graphs E Trentin, A Freno Innovations in Neural Information Paradigms and Applications, 155-182, 2009 | 7 | 2009 |
| A hybrid random field model for scalable statistical learning A Freno, E Trentin, M Gori Neural networks 22 (5-6), 603-613, 2009 | 6 | 2009 |
| Fiedler random fields: A large-scale spectral approach to statistical network modeling A Freno, M Keller, M Tommasi Advances in Neural Information Processing Systems 25, 2012 | 5 | 2012 |
| Statistical machine learning and the logic of scientific discovery A Freno Iris: european journal of Philosophy and Public Debate: 1, 2, 2009, 375-388, 2009 | 5 | 2009 |
| Markov Random Fields A Freno, E Trentin, A Freno, E Trentin Hybrid Random Fields: A Scalable Approach to Structure and Parameter …, 2011 | 4 | 2011 |
| Spectral estimation of conditional random graph models for large-scale network data A Freno, M Keller, GC Garriga, M Tommasi arXiv preprint arXiv:1210.4860, 2012 | 3 | 2012 |
| Learning to rank using Markov random fields N Freno, T Papini, M Diligenti 2011 10th International Conference on Machine Learning and Applications and …, 2011 | 2 | 2011 |
| Clothing recommendations: the Zalando case A Freno Collaborative Recommendations: Algorithms, Practical Challenges and …, 2019 | 1 | 2019 |
| Dynamic Hybrid Random Fields for the Probabilistic Graphical Modeling of Sequential Data: Definitions, Algorithms, and an Application to Bioinformatics M Bongini, A Freno, V Laveglia, E Trentin Neural Processing Letters 48, 733-768, 2018 | 1 | 2018 |
| Probability Estimation over Large-Scale Random Networks via the Fiedler Delta Statistic A Freno, M Keller, M Tommasi | | 2013 |
