LINAS BALTRUNAS, PhD
I currently work for Netflix in Los Gatos, California on personalization and various machine learning problems.
My current research areas are in various (context-aware) personalization techniques. I try to push forward the state of the art in context-aware reasoning, personalized learning to rank, tensor factorization, and diversification methods for recommender systems.
I am also interested in various aspects of large scale systems that can serve millions of users worldwide.
I love the magic moments of ideas coming to fruition.
Recsys 2019 - Copenhagen
09.16.2019 - 09.20.2019
KeyNote Speaker for CARS 2.0
Paper Accepted into REVEAL Workshop
SPEAKING ENGAGEMENTS
Recsys 2017 - Lake Como
08.27.2017 - 08.31.2017
Industry Chair
DMBI 2018 - Israel
05.10.2018
KeyNote Speaker on Context Aware Recommender Systems
RECENT NEWS
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Our paper on using RNNs for session recommendations was presented at ICLR2016.
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I recently joined Neflix, where I continue working on personalization and various machine learning problems.
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We released a new data set for context aware RS research: http://baltrunas.info/research-menu/frappe
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We released a python recsys serving engine: https://github.com/grafos-ml/frappe/
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We presented the tutorial on learning to rank at RecSys'13.
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Implementation of climf by Mark Levy(mendeley) using graphchi and Zeno Gantner(nokia) using mymedialite.
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We released Frappe: a context-aware app recommender for android into the wild.
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We got the best paper award at Recsys 2012 pdf !