Benny Kille

@bennykille

Ph.D. student @ Berlin Institute of Technology, interested in machine learning, information retrieval and knowledge discovery

Berlin, Germany
Vrijeme pridruživanja: prosinac 2010.

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  1. 26. stu 2019.
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  2. 20. ruj 2019.

    Having had a great time in Copenhagen at , the time has come to leave. Thanks , , and the rest of the organisers for the work you have put in!

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  3. proslijedio/la je Tweet
    20. ruj 2019.

    BlurM(or)e: Revisiting Gender Obfuscation in the User-Item Matrix with and Slides from our RMSE 2019 paper now available:

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  4. 20. ruj 2019.

    Last talk at has begun. Ed Malthouse and Yasaman Kamyab Hessary present their work on sponsored recommendations

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  5. 20. ruj 2019.

    Final session of has started w/ discussing recommendations at Etsy

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  6. 20. ruj 2019.

    . would like to see more domain-specific considerations in recommendation evaluation

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  7. 20. ruj 2019.

    Apparently the auto-correct ranks Alastair > last ...

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  8. 20. ruj 2019.

    The Alastair’s afternoon session starts with speaking about context adaptation in session-based recommendation

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  9. 20. ruj 2019.

    Final talk in this session by Christopher Strucks on Gender Obfuscation

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  10. 20. ruj 2019.

    . emphasises that Fairness is a System property, not something on the individual level

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  11. 20. ruj 2019.

    Next up: covering relations between multi-stakeholders and multi-sides fairness in recommendation

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  12. 20. ruj 2019.

    continues w/ Vito Walter Anelli Talking about using Generalised Cross-Entropy for fairer recommendations

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  13. 20. ruj 2019.

    . really loves his partitioning functions. Shoutout to Boltzmann, Gibbs, Kullback, and Leibler 🤔😉

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  14. 20. ruj 2019.

    Kenneth Arrow’s Theorem shows that fair voting is impossible given these assumptions

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  15. 20. ruj 2019.

    Empirical evidence that users demand more and more personalisation reported by

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  16. 20. ruj 2019.

    Keynote time w/ Google’s

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  17. 20. ruj 2019.

    Final day in Copenhagen. Let us talk about the multitude of stakeholders in recommender systems

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  18. 19. ruj 2019.

    Time is running fast. In the final talk, Nastaran Babanejad talks about emotional Features in news recommendation

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  19. 19. ruj 2019.

    Clustering Users w/ bisecting k-means adds valuable information for the “army of (multi-armed) bandits”

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  20. 19. ruj 2019.

    Michał Żmuda and Joanna Misztal-Radecka are now covering how multi-armed bandits can be used for news recommendations

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