Antonino Freno

According to our database1, Antonino Freno authored at least 17 papers between 2007 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2018
Dynamic Hybrid Random Fields for the Probabilistic Graphical Modeling of Sequential Data: Definitions, Algorithms, and an Application to Bioinformatics.
Neural Processing Letters, 2018

Clothing Recommendations: The Zalando Case.
Proceedings of the Collaborative Recommendations, 2018

2017
Practical Lessons from Developing a Large-Scale Recommender System at Zalando.
Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

2015
Techniques for dealing with incomplete data: a tutorial and survey.
Pattern Anal. Appl., 2015

One-Pass Ranking Models for Low-Latency Product Recommendations.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2012
Semiparametric Pseudo-Likelihood Estimation in Markov Random Fields.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Spectral Estimation of Conditional Random Graph Models for Large-Scale Network Data.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Hybrid Random Fields - A Scalable Approach to Structure and Parameter Learning in Probabilistic Graphical Models
Intelligent Systems Reference Library 15, Springer, ISBN: 978-3-642-20307-7, 2011

Learning to Rank Using Markov Random Fields.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

2010
Kernel-Based Hybrid Random Fields for Nonparametric Density Estimation.
Proceedings of the ECAI 2010, 2010

2009
Probabilistic Interpretation of Neural Networks for the Classification of Vectors, Sequences and Graphs.
Proceedings of the Innovations in Neural Information Paradigms and Applications, 2009

A hybrid random field model for scalable statistical learning.
Neural Networks, 2009

Scalable pseudo-likelihood estimation in hybrid random fields.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Unsupervised nonparametric density estimation: A neural network approach.
Proceedings of the International Joint Conference on Neural Networks, 2009

Scalable statistical learning: A modular bayesian/markov network approach.
Proceedings of the International Joint Conference on Neural Networks, 2009

2007
Selecting Features by Learning Markov Blankets.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2007


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