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21 - 30 of 128 search results for People aliens |u:mlg.eng.cam.ac.uk where 0 match all words and 128 match some words.

  1. Results that match 1 of 2 words

  2. Adversarial Graph Embeddings for Fair Influence Maximization over…

    https://mlg.eng.cam.ac.uk/adrian/IJCAI20_AdversarialGraphEmbeddings.pdf
    19 Jun 2024: in terms of thetotal number of people influenced, and the fraction of peopleinfluenced from both A and B communities. ... maximizing the to-tal number of influenced people, while also significantly de-creasing disparity.

  3. https://mlg.eng.cam.ac.uk/people/chaochao-lu/index.xml

    https://mlg.eng.cam.ac.uk/people/chaochao-lu/index.xml
    3 Jul 2024: Chaochao Lu | Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/people/chaochao-lu/ Chaochao Lu Wowchemy (https://wowchemy.com) en-us ... lu/avatar_hu78f90294e5b28717599f1f572dc03768_5286_270x270_fill_q75_lanczos_center.jpg Chaochao Lu

  4. You Shouldn’t Trust Me: Learning Models WhichConceal Unfairness From…

    https://mlg.eng.cam.ac.uk/adrian/ECAI20-You_Shouldn%E2%80%99t_Trust_Me.pdf
    19 Jun 2024: Let x2 be a sensitive fea-ture, such as age, given by the shape of the point: assume youngand mature people. ... 100% points are accurate (correctly, blue maturepeople are in the blue zone, red mature people are in the red zone).

  5. One-network Adversarial Fairness

    https://mlg.eng.cam.ac.uk/adrian/AAAI2019_OneNetworkAdversarialFairness.pdf
    19 Jun 2024: Here, following earlierwork, unfairness means discriminating against a particulargroup of people due to sensitive group characteristics suchas gender or race (Grgic-Hlaca et al. ... For the Adult data, a random guessing classi-fier would result in 75.9%

  6. A Unified Approach to Quantifying Algorithmic Unfairness: Measuring…

    https://mlg.eng.cam.ac.uk/adrian/KDD2018_inequality_indices.pdf
    19 Jun 2024: We furtherillustrate this point with two examples: First, by this definition amodel that assigns the same outcome to everyone is considered fair,regardless of people’s merit for different outcomes ... This offersa framework to interpolate between group

  7. https://mlg.eng.cam.ac.uk/people/jonathan-so/index.xml

    https://mlg.eng.cam.ac.uk/people/jonathan-so/index.xml
    3 Jul 2024: Jonathan So | Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/people/jonathan-so/ Jonathan So Wowchemy (https://wowchemy.com) en-us ... so/avatar_hu78f90294e5b28717599f1f572dc03768_5286_270x270_fill_q75_lanczos_center.jpg Jonathan So

  8. Working Draft 1 Accountability of AI Under the Law: ...

    https://mlg.eng.cam.ac.uk/adrian/SSRN-id3064761-Dec19.pdf
    19 Jun 2024: for most people.8 Moreover, decisions about how to define objective functions and what training data to use can introduce human error into AI decision making.9 Thus, there exist legitimate

  9. Methods for Inference in Graphical Models

    https://mlg.eng.cam.ac.uk/adrian/phd_FINAL.pdf
    19 Jun 2024: I’ve had the privilege to collaborate with wonderful people. Many thanks to Tony, Dan Ellis,.

  10. https://mlg.eng.cam.ac.uk/people/ross-clarke/index.xml

    https://mlg.eng.cam.ac.uk/people/ross-clarke/index.xml
    3 Jul 2024: Ross Clarke | Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/people/ross-clarke/ Ross Clarke Wowchemy (https://wowchemy.com) en-us ... clarke/avatar_hu78f90294e5b28717599f1f572dc03768_5286_270x270_fill_q75_lanczos_center.jpg Ross Clarke https:

  11. https://mlg.eng.cam.ac.uk/people/umang-bhatt/index.xml

    https://mlg.eng.cam.ac.uk/people/umang-bhatt/index.xml
    3 Jul 2024: Umang Bhatt | Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/people/umang-bhatt/ Umang Bhatt Wowchemy (https://wowchemy.com) en-us ... bhatt/avatar_hu78f90294e5b28717599f1f572dc03768_5286_270x270_fill_q75_lanczos_center.jpg Umang Bhatt https:/

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