Rezultati pretraživanja
  1. Everyone's talking about big data, but what really is ? Big data is the data that cannot be managed or analyzed by traditional technologies. Learn more 👉👉👉

  2. 31. sij

    We wrote a blog-post summarising our winning solution to the challenge at It seems Bayes still isn't out of fashion... 🤔

  3. 22. sij

    Only one week left to apply to our school’s PhD scholarships - this is a great opportunity to do a PhD in IR or at

  4. 29. stu 2019.

    Interesting points from about evaluation metrics of in

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  5. 9. pro 2019.

    We would like to invite you to submit a paper for the International Workshop on Algorithmic Bias in Search and Recommendation (Bias2020) to be held at . Take a look at - Deadline January 27, 2020.

  6. That RecSys Lab celebrated the open house of the new building on campus yesterday! 🥳 Our booth showcased work on recommendation fairness from our own , featuring and a giant pair of scissors during the ribbon cutting ceremony ✂️

  7. 11. stu 2019.

    My team is hiring a data engineer to work in one of the most exciting recommender systems in production out there! (ping me for details)

  8. 18. sij

    I'm looking for a postdoc to work on next generation recommender systems at in Seattle. Position starting ASAP, so apply soon!

  9. Have a look at the preprint of our extended analysis of neural algorithms. Out of 28 papers only 1 was reproducible and consistently competitive vs baselines. "A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research"

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  10. 4. sij
    Odgovor korisniku/ci

    Place ratings in are usually very accurate and reliable because ’s algorithm takes into account many implicit signals and does not just rely on reviews. It’s all laid out in this post by & :

  11. 21. sij
  12. 6. pro 2019.
  13. 18. pro 2019.

    Work with us . 2-3 year postdoc Research Fellow position for an Australian Research Council Discovery Project in multi-resolution situation recognition with me, Yongli Ren

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  14. 3. pro 2019.
  15. 29. stu 2019.

    And the summary! Valid points about business values and .

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  16. prije 6 sati

    at the team, we are looking for a Recommender Systems product manager

  17. 25. stu 2019.

    Listening to talking about “Revisiting offline evaluation for implicit feedback recommender systems”

  18. 4. pro 2019.

    hey folks we are looking for a backend engineer for my team! Please reach out if you are interested

  19. It's ! 🖐️💻🎉 Today we are featuring , who is researching how to achieve fairness in algorithms, while considering different stakeholders. Her favorite / most influential work? Check it out!

  20. 14. sij

    Recommendations made through graph embeddings: at the Torino chapter of the databeers

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