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41 - 60 of 98 search results for KaKaoTalk:PC53 24 / |u:mlg.eng.cam.ac.uk where 0 match all words and 98 match some words.

  1. Results that match 1 of 2 words

  2. Conditions Beyond Treewidth for Tightness of Higher-order LP…

    https://mlg.eng.cam.ac.uk/adrian/conditions.pdf
    19 Jun 2024: Conditions Beyond Treewidth for Tightness of Higher-order LP Relaxations. Mark Rowland Aldo Pacchiano Adrian WellerUniversity of Cambridge UC Berkeley University of Cambridge. Abstract. Linear programming (LP) relaxations are a pop-ular method to

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

    https://mlg.eng.cam.ac.uk/adrian/SSRN-id3064761-Dec19.pdf
    19 Jun 2024: 24. Furthermore, an explanation must also provide the correct type of information in order for it to be useful. ... 24 Wachter, Right to Explanation, supra note 18. For a discussion about legibility of algorithmic systems more broadly, see Gianclaudio

  4. Geometrically Coupled Monte Carlo Sampling Mark Rowland∗University of …

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS18-gcmc.pdf
    19 Jun 2024: Geometrically Coupled Monte Carlo Sampling. Mark RowlandUniversity of Cambridgemr504@cam.ac.uk. Krzysztof ChoromanskiGoogle Brain Roboticskchoro@google.com. François ChalusUniversity of Cambridgechalusf3@gmail.com. Aldo PacchianoUniversity of

  5. Clamping Improves TRW and Mean Field Approximations Adrian Weller∗ ...

    https://mlg.eng.cam.ac.uk/adrian/clamp_aistats_final.pdf
    19 Jun 2024: Journal of Automated Reasoning, 24(1-2):225–275, 2000. N. Ruozzi. The Bethe partition function of log-supermodular graphical models.

  6. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/0910/lect01.pdf
    19 Nov 2023: Ghahramani & Rasmussen (CUED) Lecture 1: Introduction to Machine Learning January 14th, 2010 24 / 26.

  7. The Unreasonable Effectiveness of StructuredRandom Orthogonal…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-unreasonable-effectiveness.pdf
    19 Jun 2024: sin2(φ) cos2(ϕ1) cos2(ϕ2) sin2(ϕ1)cos2(ϕ2) sin. 2(ϕ1) sin2(φ) cos2(ϕ1). (24). This observation greatly simplifies the integral from Equation (22) involving the term

  8. Methods for Inference in Graphical Models

    https://mlg.eng.cam.ac.uk/adrian/phd_FINAL.pdf
    19 Jun 2024: 3 Additional Background 24. 3.1 MAP Inference and Tractable Cases. 24.

  9. - Machine Learning 4F13, Spring 2014

    https://mlg.eng.cam.ac.uk/teaching/4f13/1314/lect0102.pdf
    19 Nov 2023: 4. 3. 2. 1. 0. 1. 2. 3. Rasmussen and Ghahramani Lecture 1 and 2: Probabilistic Regression 24 / 36.

  10. An Introduction to LP Relaxations for MAP Inference

    https://mlg.eng.cam.ac.uk/adrian/2018-MLSALT4-AW2-LP.pdf
    19 Jun 2024: x3. x4. x5. x6. s. balanced almost balanced(attractive up to flipping) 24 / 41.

  11. - Machine Learning 4F13, Spring 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1415/lect0102.pdf
    19 Nov 2023: 1. 0. 1. 2. 3. Samples from the posteriorRasmussen and Ghahramani Lecture 1 and 2: Probabilistic Regression 24 / 37.

  12. - Machine Learning 4F13, Michaelmas 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1516/lect0102.pdf
    19 Nov 2023: 1. 0. 1. 2. 3. Samples from the posteriorGhahramani Lecture 1 and 2: Probabilistic Regression 24 / 38.

  13. Gauged Mini-Bucket Elimination for Approximate Inference Sungsoo Ahn…

    https://mlg.eng.cam.ac.uk/adrian/Gauge_for_Holder_Inference.pdf
    19 Jun 2024: We call these methods collectively Z-invariant methods. See [23, 24, 25] for discussions ofthe differences and relations between these methods. ... 24] G. David Forney Jr and Pascal O. Vontobel. Par-tition functions of normal factor graphs.

  14. Human Perceptions of Fairness in Algorithmic Decision Making: A Case…

    https://mlg.eng.cam.ac.uk/adrian/WWW18-HumanPerceptions.pdf
    19 Jun 2024: 47% 68% 70%B.S. 51% 32% 30%Liberal 57% 37% 33%Conservative 17% 24% 29%Moderate 21% 33% 34%Other 5% 6% 4%. ... Substance Abuse 4.84 0.08 0.07 0.10 0.24 0.07 0.68 0.26 0.22 0.20 0.07 0.284.

  15. An introduction to Flow Matching · Cambridge MLG Blog

    https://mlg.eng.cam.ac.uk/blog/2024/01/20/flow-matching.html
    12 Apr 2024: Figure 24: One-sided conditioning (Lipman et al., 2022). Figure 25: Two-sided conditioning (Tong et al., 2023).

  16. Gaussian Process

    https://mlg.eng.cam.ac.uk/teaching/4f13/1617/gaussian%20process.pdf
    19 Nov 2023: 64. 20. 24. 6. 6. 4. 2. 0. 2. 4. 6.

  17. Natural-Gradient Variational Inference 2: ImageNet-scale · Cambridge…

    https://mlg.eng.cam.ac.uk/blog/2021/11/24/ngvi-bnns-part-2.html
    12 Apr 2024: Published on 24 November 2021. This is the blog of the Cambridge Machine Learning Group.

  18. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/0809/lect01.pdf
    19 Nov 2023: Ghahramani & Rasmussen (CUED) Lecture 1: Introduction to Machine Learning January 16th, 2009 24 / 26.

  19. Gaussian Process

    https://mlg.eng.cam.ac.uk/teaching/4f13/2324/gaussian%20process.pdf
    19 Nov 2023: 64. 20. 24. 6. 6. 4. 2. 0. 2. 4. 6.

  20. Gaussian Processes — a brief introduction

    https://mlg.eng.cam.ac.uk/teaching/4f13/2324/gp.pdf
    19 Nov 2023: 64. 20. 24. 6. 6. 4. 2. 0. 2. 4. 6. ... Rasmussen Gaussian Processes October 23th, 2023 24 / 27. 43. 21.

  21. 3F3: Signal and Pattern Processing Lecture 5: Dimensionality…

    https://mlg.eng.cam.ac.uk/teaching/3f3/1011/lect5.pdf
    19 Nov 2023: Dataset Data dim. Sample size MLE Regression Corr. dim.Swiss roll 3 1000 2.1(0.02) 1.8(0.03) 2.0(0.24)Faces 64 64 698 4.3

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