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31 - 40 of 61 search results for TALK:PC53 20 |u:mlg.eng.cam.ac.uk where 0 match all words and 61 match some words.

  1. Results that match 1 of 2 words

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

    https://mlg.eng.cam.ac.uk/adrian/Gauge_for_Holder_Inference.pdf
    19 Jun 2024: Methods using reparametrizations [18], gauge transfor-mations (GT) [19, 20] or holographic transformations(HT) [21, 22] have been explored. ... With these constraints,the partition function is known to be invariant underthe transformation [19, 20], i.e.,.

  3. The Case for Process Fairness in Learning:Feature Selection for ...

    https://mlg.eng.cam.ac.uk/adrian/grgic.pdf
    19 Jun 2024: Age 41% 67% 33%Gender 28% 61% 26%Race 17% 50% 20%. Table 4: Comparing judgment of fairness of each feature, of 46 female users, when they have differentknowledge about the

  4. 2018 Formatting Instructions for Authors Using LaTeX

    https://mlg.eng.cam.ac.uk/adrian/AIES18-crowd_signals.pdf
    19 Jun 2024: 20. PD. F. Retweeters. Repliers. Followers. (B) Low consensus tweet. Figure 3: Distributions of political leanings of different au-diences for the following news posts: (A) High consensus:“Trump ordered emergency ... repeated 20 timeswith different

  5. An Introduction to LP Relaxations for MAP Inference

    https://mlg.eng.cam.ac.uk/adrian/2018-MLSALT4-AW2-LP.pdf
    19 Jun 2024: 20 / 41. Stylized illustration of polytopes. marginal polytope M = Lnglobal consistency. ... 20 / 41. When is the LP tight? For a model without cycles, local polytope L2=M marginalpolytope, hence the basic LP (‘first order’) is always tight.

  6. Uprooting and Rerooting Graphical Models

    https://mlg.eng.cam.ac.uk/adrian/Wel16_Uproot.pdf
    19 Jun 2024: 5. 10. 15. 20. 25Original MMworstmaxWmaxtWbest. maximum edge strength Wmax. 2 4 8 12 160. ... 20. 40. 60. 80Original MMworstmaxWmaxtWbest. maximum edge strength Wmax. 2 4 8 12 160.

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

    https://mlg.eng.cam.ac.uk/adrian/clamp_aistats_final.pdf
    19 Jun 2024: 20. 25. best. worst. pseudo. greedy. med. ium. (49). 0 1 2 3 4 58. ... 20. 30. 40. best. worst. pseudo. greedy. 0 1 2 3 4 520.

  8. Transparency: Motivations and Challenges? Adrian…

    https://mlg.eng.cam.ac.uk/adrian/transparency.pdf
    19 Jun 2024: Exciting work has begun to explore this direction, lookingfor ways to enable multiple agents to cooperate effectively [20, 28, 47]. ... 20. Evtimova, K., Drozdov, A., Kiela, D., Cho, K.: Emergent communication in amulti-modal, multi-step referential game.

  9. Now You See Me (CME): Concept-based Model Extraction

    https://mlg.eng.cam.ac.uk/adrian/AIMLAI20-CME.pdf
    19 Jun 2024: Model ExtractionModel extraction techniques use rules [20, 21, 22], de-cision trees [23, 24], or other more readily explainablemodels [25] to approximate complex models, in orderto study their behaviour. ... 20] R. Andrews, J. Diederich, A. B. Tickle,

  10. Structured Evolution with Compact Architectures for Scalable Policy…

    https://mlg.eng.cam.ac.uk/adrian/structured_icml_full.pdf
    19 Jun 2024: and Wild, Stefan M. Benchmarkingderivative-free optimization algorithms. SIAM Journalon Optimization, 20(1):172–191, 2009.

  11. Clamping Variables and Approximate Inference Adrian WellerColumbia…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS14-clamp.pdf
    19 Jun 2024: 00.5. 1. 00.5. 10. 10. 20. qj. v=1/Qij, W=3. qi. (b) W=3. ... 10. 20. 30. 40. max. Originalavg ClampmaxW Clampbest Clampworst ClampMpower. interaction strength W.

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