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31 - 40 of 70 search results for Economics Syllabus |u:mlg.eng.cam.ac.uk where 7 match all words and 63 match some words.

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  2. Machine Learning 4f13 Lent 2014

    https://mlg.eng.cam.ac.uk/teaching/4f13/1314/
    19 Nov 2023: LECTURE SYLLABUS. This year, the exposition of the material will be centered around three specific machine learning areas: 1) supervised non-paramtric probabilistic inference using Gaussian processes, 2) the TrueSkill ranking

  3. Machine Learning 4f13 Lent 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1415/
    19 Nov 2023: LECTURE SYLLABUS. This year, the exposition of the material will be centered around three specific machine learning areas: 1) supervised non-parametric probabilistic inference using Gaussian processes, 2) the TrueSkill ranking

  4. Probabilistic Machine Learning 4f13 Michaelmas 2016

    https://mlg.eng.cam.ac.uk/teaching/4f13/1617/
    19 Nov 2023: Lecture Syllabus. This year, the exposition of the material will be centered around three specific machine learning areas: 1) supervised non-parametric probabilistic inference using Gaussian processes, 2) the TrueSkill ranking

  5. Probabilistic Machine Learning 4f13 Michaelmas 2017

    https://mlg.eng.cam.ac.uk/teaching/4f13/1718/
    19 Nov 2023: Lecture Syllabus. This year, the exposition of the material will be centered around three specific machine learning areas: 1) supervised non-parametric probabilistic inference using Gaussian processes, 2) the TrueSkill ranking

  6. Clamping Variables and Approximate Inference Adrian WellerColumbia…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS14-clamp.pdf
    6 May 2024: In UAI, 2009. P. Milgrom. The envelope theorems. Department of Economics, Standford University, Mimeo, 1999.

  7. Probabilistic Machine Learning 4f13 Michaelmas 2018

    https://mlg.eng.cam.ac.uk/teaching/4f13/1819/
    19 Nov 2023: Lecture Syllabus. This year, the exposition of the material will be centered around three specific machine learning areas: 1) supervised non-parametric probabilistic inference using Gaussian processes, 2) the TrueSkill ranking

  8. Probabilistic Machine Learning 4f13 Michaelmas 2021

    https://mlg.eng.cam.ac.uk/teaching/4f13/2122/
    19 Nov 2023: Lecture Syllabus. This year, the exposition of the material will be centered around three specific machine learning areas: 1) supervised non-parametric probabilistic inference using Gaussian processes, 2) the TrueSkill ranking

  9. nips2007-final.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/SilChuGha08.pdf
    27 Jan 2023: This setup is very closely related to the classicseemingly unrelated regressionmodel popular in economics [12].

  10. From Parity to Preference-based Notionsof Fairness in Classification…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-from-parity-to-preference.pdf
    6 May 2024: In this paper, we draw inspiration from the fair-division and envy-freeness literature in economics and game theory and proposepreference-based notions of fairness—given the choice between various sets ... In this work, we introduce, formalize and

  11. Orthogonal Estimation of Wasserstein Distances Mark Rowland∗1 Jiri…

    https://mlg.eng.cam.ac.uk/adrian/AISTATS19-slicedwasserstein.pdf
    6 May 2024: physics (Jordan et al., 1998) and economics(Galichon, 2016), and are increasingly used in machinelearning (Arjovsky et al., 2017; Gulrajani et al., 2017;Peyré and Cuturi, 2018).

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