Workshop on Deep Learning for Recommender Systems

We believe that deep learning is one of the next big things in recommendation systems technology. The past few years have seen the tremendous success of deep neural networks in a number of complex tasks such as computer vision, natural language processing and speech recognition. Despite this, only little work has been published on deep learning methods for the recommender systems. Notable exceptions are deep learning methods for music recommendation, and session-based recommendation.

The aim of the workshop is to encourage the application of deep learning techniques in recommender systems, to promote research in novel deep learning methods specific to recommender systems, and to bring together researchers from the recommender systems and deep learning communities.

  • Alexandros Karatzoglou, Telefonica Research, Spain
  • Bal√°zs Hidasi, Gravity R&D, Hungary
  • Domonkos Tikk, Gravity R&D, Hungary
  • Oren Sar-Shalom, IBM Research, Israel
  • Haggai Roitman, IBM Research, Isreal
  • Bracha Shapira, Ben-Gurion University, Isreal
  • Lior Rokach, Ben-Gurion University, Isreal


Thursday, Sept 15, 2016, 09:00-12:30


IBM (Aud B)

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