Unifying collaborative and content-based filtering. - Justin Basilico; Thomas Hofmann 001 (ICML, 2004)

A joint framework for collaborative and content filtering. - Justin Basilico; Thomas Hofmann 001 (SIGIR, 2004)

Collaborative Machine Learning. - Thomas Hofmann 001; Justin Basilico (From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments, 2005)

Using Context to Identify Difficult Driving Situations in Unstructured Environments. - Kevin R. Dixon; Justin D. Basilico; J. Chris Forsythe; Wilhelm E. Kincses (HCI (16), 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 (HCI (16), 2009)

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 (ICDM, 2011)

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)

Recommender Systems in Industry: A Netflix Case Study. - Xavier Amatriain; Justin Basilico (Recommender Systems Handbook, 2015)

Past, Present, and Future of Recommender Systems: An Industry Perspective. - Xavier Amatriain; Justin Basilico (RecSys, 2016)

Recommending for the World. - Justin Basilico; Yves Raimond (RecSys, 2016)

Using Navigation to Improve Recommendations in Real-Time. - Chao-Yuan Wu; Christopher V. Alvino; Alexander J. Smola; Justin Basilico (RecSys, 2016)

Déjà Vu: The Importance of Time and Causality in Recommender Systems. - Justin Basilico; Yves Raimond (RecSys, 2017)

Artwork personalization at netflix. - Fernando Amat Gil; Ashok Chandrashekar; Tony Jebara; Justin Basilico (RecSys, 2018)

2nd International Workshop on Industrial Recommendation Systems (IRS). - Jianpeng Xu; Lingfei Wu 001; Xiaolin Pang 001; Mohit Sharma 002; Dawei Yin; George Karypis; Justin Basilico; Philip S. Yu (KDD, 2021)

Accordion: A Trainable Simulator forLong-Term Interactive Systems. - James McInerney; Ehtsham Elahi; Justin Basilico; Yves Raimond; Tony Jebara (RecSys, 2021)

RecSysOps: Best Practices for Operating a Large-Scale Recommender System. - Mohammad Saberian; Justin Basilico (RecSys, 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)

Workshop on Learning and Evaluating Recommendations with Impressions (LERI). - Maurizio Ferrari Dacrema; Pablo Castells; Justin Basilico; Paolo Cremonesi (RecSys, 2023)

Reward innovation for long-term member satisfaction. - Gary Tang; Jiangwei Pan; Henry Wang; Justin Basilico (RecSys, 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 (RecSys, 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, 2023)