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31 - 38 of 38 search results for TALK:ZA31 24 / |u:mlg.eng.cam.ac.uk where 0 match all words and 38 match some words.

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  2. Unifying Orthogonal Monte Carlo Methods

    https://mlg.eng.cam.ac.uk/adrian/ICML2019-unified.pdf
    16 May 2024: E[x̃λỹλx̃λvỹλv x̃. 2λỹ. 2λv. ] (24)We next show the following. Lemma A.7.

  3. Uprooting and Rerooting Higher-Order GraphicalModels Mark…

    https://mlg.eng.cam.ac.uk/adrian/uprooting-higher-order.pdf
    16 May 2024: 4], which relates to generalized belief propagation,24) and MAP inference (using loopy belief propagation, LBP [9]). ... InArtificial Intelligence and Statistics (AISTATS), 2016. [24] J. Yedidia, W. Freeman, and Y.

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

    https://mlg.eng.cam.ac.uk/adrian/conditions.pdf
    16 May 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

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

    https://mlg.eng.cam.ac.uk/adrian/SSRN-id3064761-Dec19.pdf
    16 May 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

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

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS18-gcmc.pdf
    16 May 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

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

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

  8. The Unreasonable Effectiveness of StructuredRandom Orthogonal…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-unreasonable-effectiveness.pdf
    16 May 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

  9. Methods for Inference in Graphical Models

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

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