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31 - 40 of 58 search results for TALK:PC53 20 |u:mlg.eng.cam.ac.uk where 0 match all words and 58 match some words.

  1. Results that match 1 of 2 words

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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,

  7. 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.

  8. 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.

  9. Ode to an ODE Krzysztof Choromanski ∗Robotics at Google ...

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS20-ODEtoODE.pdf
    19 Jun 2024: CoRR, abs/2005.01906, 2020. [20] Emilien Dupont, Arnaud Doucet, and Yee Whye Teh. ... SIAM J. Matrix Analysis Applications, 20(2):303–353, 1998. [22] Chris Finlay, Jörn-Henrik Jacobsen, Levon Nurbekyan, and Adam M.

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

    https://mlg.eng.cam.ac.uk/adrian/WWW18-HumanPerceptions.pdf
    19 Jun 2024: 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. ... Criminal Attitudes 3.63 0.22 0.12 0.16 0.51 0.09 0.40 0.20 0.11 0.09 0.03 0.157.

  11. One-network Adversarial Fairness

    https://mlg.eng.cam.ac.uk/adrian/AAAI2019_OneNetworkAdversarialFairness.pdf
    19 Jun 2024: disc(P0,P1) disc(P̂0,P̂1). RadD0(Err(H)). 2+. log(1/δ). n. RadD1(Err(H)). 2+. log(1/δ). n(20). disc(P0,P1) disc(P̂0,P̂1) 2. ... of 60% of the data is reserved for training, 20%for validation and 20% for testing.

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