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21 - 40 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. 13 Feb 2023: Low Density Separation (Chapelle. Appearing in Proceedings of the 24 th International Confer-ence on Machine Learning, Corvallis, OR, 2007. ... 42.72 13.49 4.95 3.79 9.68 21.99 35.17 24.38Data dep.
  3. - Machine Learning 4F13, Spring 2014

    https://mlg.eng.cam.ac.uk/teaching/4f13/1314/lect0304.pdf
    19 Nov 2023: 1. 0. 1. 2M=0. 1 0 1 24. 2. 0. 2. ... 1. 2M=0. 1 0 1 24. 2. 0. 2. 4. M=1.
  4. - Machine Learning 4F13, Spring 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1415/lect0304.pdf
    19 Nov 2023: 1. 0. 1. 2M=0. 1 0 1 24. 2. 0. 2. ... 1. 2M=0. 1 0 1 24. 2. 0. 2. 4. M=1.
  5. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/1213/lect0304.pdf
    19 Nov 2023: 1. 2M=0. 1 0 1 24. 2. 0. 2. 4. M=1. ... p(x, y)dy = p(x):. wkp(w)dw =. wk(. p(wk, w/k)dw/k. )dwk =. wkp(wk)dwk. Rasmussen & Ghahramani (CUED) Lecture 3 and 4: Gaussian Processes 24 / 32.
  6. Bayesian Learning of Model Structure Zoubin GhahramaniGatsb y…

    https://mlg.eng.cam.ac.uk/zoubin/talks/cmu-talk.pdf
    27 Jan 2023: 4 5 3 5 3 5 4 3. 24. 34. 33. ... 32. 24. 45. 54. 35. 55. 34. 44. 44. 4. 35.
  7. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/1112/lect0304.pdf
    19 Nov 2023: 1. 2M=0. 1 0 1 24. 2. 0. 2. 4. M=1. ... p(x, y)dy = p(x):. wkp(w)dw =. wk(. p(wk, w/k)dw/k. )dwk =. wkp(wk)dwk. Quiñonero-Candela & Rasmussen (CUED) Lecture 3 and 4: Gaussian Processes 24 /
  8. 3F3: Signal and Pattern Processing Lecture 1: Introduction to ...

    https://mlg.eng.cam.ac.uk/teaching/3f3/1011/lect1.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
  9. book

    https://mlg.eng.cam.ac.uk/pub/pdf/PerGhaPon07.pdf
    13 Feb 2023: 1.23). subject to:. wt φt(xn, ynt) wt φt(xn, yt) Mynt,yt ξnt n, t, yt (1.24). ... We end up having a significant reduction in the number ofconstraints2 in our optimisation formulation for CGMs in (1.23)-(1.24).
  10. Marc P. Deisenroth, Carl E. Rasmussen, and Jan Peters: ...

    https://mlg.eng.cam.ac.uk/pub/pdf/DeiRasPet08.pdf
    13 Feb 2023: pages 19–24, Bruges, Belgium, April 2008. Model-Based Reinforcement Learning withContinuous States and Actions.
  11. G:\bioinformatics\ISMB\btq210.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/SavGhaGrietal10.pdf
    13 Feb 2023: 5634 2 2.6108 22/23 15/84 Nucleus32991 2 7.9105 18/23 24/84 Macromolecular complex. ... BMC Bioinformatics, 8,283. i165. by on July 24, 2010 http://bioinform. atics.oxfordjournals.orgDownloaded from.
  12. paper.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/KimGha08.pdf
    13 Feb 2023: GPC log-ev -24.40.6 -41.80.8 -51.81.1 -60.21.0error(%) 3.700.36 4.900.77 7.500.88 8.151.42. robust log-ev ... MS-robust- log-ev -24.40.6 -41.00.7 -50.50.7 -58.60.8GPC error(%) 3.700.36 4.540.62 6.760.76 6.850.73.
  13. Bayesian Hierarchical Clustering Katherine A. Heller…

    https://mlg.eng.cam.ac.uk/zoubin/papers/icml05heller.pdf
    27 Jan 2023: 1 2 3 4 5 6 8 9 10 7 11 12 13 14 15 16 18 20 19 17 21 22 23 24 25 26 270. ... 0.2231.24. 3.6. 59.9. 0 1 2 3 4 5 6 74.
  14. grasshopper.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/GolZhuVanAnd07.pdf
    13 Feb 2023: Afterexamining the results for all 24 configurations, weselected the best one:α = 0.25 andλ = 0.5. ... of 11DUC 2004 Task 4b 24 0.4067 [0.3883, 0.4251] Between 2 & 3 of 11.
  15. LNCS 5342 - Outlier Robust Gaussian Process Classification

    https://mlg.eng.cam.ac.uk/pub/pdf/KimGha08a.pdf
    13 Feb 2023: label-change rate(%) 0 5 10 15SVM error(%) 4.070.60 5.090.96 6.761.10 8.801.13GPC log-ev -24.40.6 -41.80.8 -51.81.1 ... MS-robust- log-ev -24.40.6 -41.00.7 -50.50.7 -58.60.8GPC error(%) 3.700.36 4.540.62 6.760.76 6.850.73.
  16. newroyftp.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/RGBN.pdf
    27 Jan 2023: A factor analyzer with 24 hidden units discoversglobal features with both excitatory and inhibitory components (gure 9a). ... a) Weights from the top layer hidden unit to the 24 middle-layer hidden units.
  17. 13 Feb 2023: Publications, Machine Learning Group, Department of Engineering, Cambridge. current group:. [former members:. [by year:. [2022. James Urquhart Allingham, Florian Wenzel, Zelda E Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel,
  18. Time-Sensitive Dirichlet Process Mixture Models Xiaojin Zhu Zoubin…

    https://mlg.eng.cam.ac.uk/zoubin/papers/tdpmTR.pdf
    27 Jan 2023: w(t, c) =. i:ti<t,si=c. k(t ti) =. eλ(tti) (24). λw(t, c) =. i:ti<t,si=c. (t ti)eλ(tti) (25). We then take a
  19. Bayesian Knowledge Corroboration with LogicalRules and User Feedback…

    https://mlg.eng.cam.ac.uk/pub/pdf/KasVanGraHer10.pdf
    13 Feb 2023: While [23, 24] represent the formalism of first-orderlogic by factor graph models, [27] and [29] deal with Bayesian networks appliedto first-order logic. ... 1094–1099. AAAI Press(2008). 24. Domingos, P., Richardson, M.: Markov Logic Networks.
  20. 1 Robust Filtering and Smoothing with Gaussian Processes Marc ...

    https://mlg.eng.cam.ac.uk/pub/pdf/DeiTurHubetal12.pdf
    13 Feb 2023: Using the definition of S in (24), the productof the two Gaussians in (36) results in a new (unnormalized) Gaussianc14 N(xt1 |ψi, Ψ) with. ... 24] J. Kocijan, R. Murray-Smith, C. E. Rasmussen, and B. Likar, “PredictiveControl with Gaussian Process
  21. The Infinite Hidden Markov Model Matthew J. Beal Zoubin ...

    https://mlg.eng.cam.ac.uk/pub/pdf/BeaGhaRas02.pdf
    13 Feb 2023: The Infinite Hidden Markov Model. Matthew J. Beal Zoubin Ghahramani Carl Edward Rasmussen. Gatsby Computational Neuroscience UnitUniversity College London. 17 Queen Square, London WC1N 3AR, Englandhttp://www.gatsby.ucl.ac.uk. {m.beal,zoubin,edward

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