Justin Basilico

According to our database, Justin Basilico authored at least 21 papers between 2004 and 2023.

Collaborative distances:

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

2023

Report on the Workshop on Learning and Evaluating Recommendations with Impressions (LERI) at RecSys 2023.

Maurizio Ferrari Dacrema, Pablo Castells, Justin Basilico, Paolo Cremonesi

SIGIR Forum, December, 2023

Navigating the Feedback Loop in Recommender Systems: Insights and Strategies from Industry Practice.

Ding Tong, Qifeng Qiao, Ting-Po Lee, James McInerney, Justin Basilico

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

Reward innovation for long-term member satisfaction.

Gary Tang, Jiangwei Pan, Henry Wang, Justin Basilico

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

Workshop on Learning and Evaluating Recommendations with Impressions (LERI).

Maurizio Ferrari Dacrema, Pablo Castells, Justin Basilico, Paolo Cremonesi

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

2021

Deep Learning for Recommender Systems: A Netflix Case Study.

Harald Steck, Linas Baltrunas, Ehtsham Elahi, Dawen Liang, Yves Raimond, Justin Basilico

AI Mag., 2021

RecSysOps: Best Practices for Operating a Large-Scale Recommender System.

Mohammad Saberian, Justin Basilico

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Accordion: A Trainable Simulator forLong-Term Interactive Systems.

James McInerney, Ehtsham Elahi, Justin Basilico, Yves Raimond, Tony Jebara

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

2nd International Workshop on Industrial Recommendation Systems (IRS).

Jianpeng Xu, Lingfei Wu, Xiaolin Pang, Mohit Sharma, Dawei Yin, George Karypis, Justin Basilico, Philip S. Yu

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2018

Artwork personalization at netflix.

Fernando Amat Gil, Ashok Chandrashekar, Tony Jebara, Justin Basilico

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

2017

Déjà Vu: The Importance of Time and Causality in Recommender Systems.

Justin Basilico, Yves Raimond

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

2016

Using Navigation to Improve Recommendations in Real-Time.

Chao-Yuan Wu, Christopher V. Alvino, Alexander J. Smola, Justin Basilico

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

Recommending for the World.

Justin Basilico, Yves Raimond

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

Past, Present, and Future of Recommender Systems: An Industry Perspective.

Xavier Amatriain, Justin Basilico

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

2015

Recommender Systems in Industry: A Netflix Case Study.

Xavier Amatriain, Justin Basilico

Proceedings of the Recommender Systems Handbook, 2015

2014

DeepQA Jeopardy! Gamification: A Machine-Learning Perspective.

Aaron K. Baughman, Wesley Chuang, Kevin R. Dixon, Zachary Benz, Justin Basilico

IEEE Trans. Comput. Intell. AI Games, 2014

2011

COMET: A Recipe for Learning and Using Large Ensembles on Massive Data.

Justin D. Basilico, M. Arthur Munson, Tamara G. Kolda, Kevin R. Dixon, W. Philip Kegelmeyer

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2009

Improved Team Performance Using EEG- and Context-Based Cognitive-State Classifications for a Vehicle Crew.

Kevin R. Dixon, Konrad Hagemann, Justin Basilico, J. Chris Forsythe, Siegfried Rothe, Michael Schrauf, Wilhelm E. Kincses

Proceedings of the Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience, 2009

Using Context to Identify Difficult Driving Situations in Unstructured Environments.

Kevin R. Dixon, Justin D. Basilico, J. Chris Forsythe, Wilhelm E. Kincses

Proceedings of the Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience, 2009

2005

Collaborative Machine Learning.

Thomas Hofmann, Justin Basilico

Proceedings of the From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments, 2005

2004

A joint framework for collaborative and content filtering.

Justin Basilico, Thomas Hofmann

Proceedings of the SIGIR 2004: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2004

Unifying collaborative and content-based filtering.

Justin Basilico, Thomas Hofmann

Proceedings of the Machine Learning, 2004