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61 - 70 of 261 search results for KaKaoTalk:ZA31 24 24 |u:mlg.eng.cam.ac.uk where 0 match all words and 261 match some words.

  1. Results that match 2 of 3 words

  2. Bayesian Learning in Undirected Graphical Models:Approximate MCMC…

    https://mlg.eng.cam.ac.uk/pub/pdf/MurGha04a.pdf
    13 Feb 2023: Pattern Recogni-tion Letters, 24:1251–1259, 2003. [19] David Edwards and Tomáš Havránek.

  3. analogy-aistats2007.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/analogy-aistats2007.pdf
    27 Jan 2023: C1 C2 RB SB1 SB2 C1 C2 RB SB1 SB2. student course f aculty projectcornell 0.87 0.61 0.87 0.84 0.80 0.19 0.04 0.24 ... 0.18 0.18texas 0.55 0.54 0.77 0.62 0.48 0.24 0.07 0.29 0.07 0.12.

  4. PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

    https://mlg.eng.cam.ac.uk/pub/pdf/ParRasPetDoy18.pdf
    13 Feb 2023: 24. 26. 28. 30. Particle value estimateMoment matching value estimate. Distance in parameter space ( ). Val. ue. (a). -0.15 -0.1 -0.053.3. 3.35. 3.4. 3.45. ... COST FUNCTION NOISE MULTIPLIER PILCO RP RPFS GR GRFS LR TP TPσf TPσnANGLE COST k = 102 0.88 0

  5. SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases

    https://mlg.eng.cam.ac.uk/pub/pdf/LacPalDav13a.pdf
    13 Feb 2023: Finally, we mention thatPeralta [24] aligned the movie database MovieLens to IMDbthrough a combination of steps of manual cleaning with someautomation.

  6. vietri.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/vietri.pdf
    27 Jan 2023: Wewill deal exclusively with directed graphical models in this paper.4. texts [41, 24, 19] for details.Assume we observe some evidence: the value of some variables in the network.The ... If the parents of n are fp1; : : :;pkg and thechilden of n are fc1;

  7. gppl.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/icml05chuwei-pl.pdf
    27 Jan 2023: f MAPa = Σaβa (24). where βa =. ni=1. gij=1 ln Φ(z. ... de-fined as in (24) at θ.

  8. Relational Learning with Gaussian Processes Wei ChuCCLS Columbia…

    https://mlg.eng.cam.ac.uk/pub/pdf/ChuSinGhaetal07.pdf
    13 Feb 2023: 28. 26. 24. 22. 20. 18. κ. log P(E). log P(E,Y).

  9. coverage.eps

    https://mlg.eng.cam.ac.uk/pub/pdf/SilHelGhaetal10.pdf
    13 Feb 2023: student course f aculty projectcornell 0.87 0.82 0.87 0.82 0.80 0.19 0.18 0.24 0.18 0.18texas 0.62 0.32 0.77 ... 0.55 0.54 0.24 0.21 0.29 0.12 0.12.

  10. LNAI 3944 - Evaluating Predictive Uncertainty Challenge

    https://mlg.eng.cam.ac.uk/pub/pdf/QuiRasSinetal06.pdf
    13 Feb 2023: 101. 100. Outaouais (regression). NLPD. nMSE. (c). 0.22 0.24 0.26 0.28 0.30.2.

  11. Bayesian Gaussian Process Classificationwith the EM-EP…

    https://mlg.eng.cam.ac.uk/pub/pdf/KimGha06a.pdf
    13 Feb 2023: Itsgeneralized version which is convergent but slower hasbeen proposed [24]. 3.2 EP for Gaussian Process Classification. ... 00 0. CfJ. 24. 35; ð37Þ. where Cfj is a covariance matrix of latent values related to.

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