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31 - 40 of 261 search results for TALK:ZA31 24 / |u:mlg.eng.cam.ac.uk where 0 match all words and 261 match some words.

  1. Results that match 1 of 2 words

  2. Discovering temporal patterns of differential geneexpression in…

    https://mlg.eng.cam.ac.uk/pub/pdf/SteDenMcHetal09.pdf
    13 Feb 2023: cinerea spore suspension (or mock-inoculated) and harvested every 2 hr upto 48 hr post-inoculation for a total of 24 time points.

  3. PILCO: A Model-Based and Data-Efficient Approach to Policy Search

    https://mlg.eng.cam.ac.uk/pub/pdf/DeiRas11.pdf
    13 Feb 2023: Ext [c(xt)] =. c(xt)N. (xt |µt, Σt. )dxt , (24). t = 0,. ... 10)–(12), (24).7: Gradient-based policy improvement, see. Sec. 2.3: get dJπ(θ)/ dθ, Eqs.

  4. 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.

  5. The Infinite Hidden Markov Model Matthew J. Beal Zoubin ...

    https://mlg.eng.cam.ac.uk/zoubin/papers/ihmm.pdf
    27 Jan 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

  6. Sequential Decisions

    https://mlg.eng.cam.ac.uk/zoubin/SALD/week13sequential.pdf
    27 Jan 2023: solutions – the latter relating to “improper” priors! 24. Appendix: Background on the Von Neumann - Morgenstern theory of cardinal.

  7. Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning

    https://mlg.eng.cam.ac.uk/pub/pdf/ZhuKanGha04a.pdf
    13 Feb 2023: 50.27 (86) 0.24 (92) 0.15 0.18 0.40 (85) 0.02 0.12 0.09. ... 0.27 (26) 0.13 (25) 0.03 0.11 0.31 (24) -0.89 -0.80 -0.65100 64.6 2.1 59.0 3.6 58.5 2.9

  8. A Brief Overview of Nonparametric Bayesian Models NIPS 2009 ...

    https://mlg.eng.cam.ac.uk/zoubin/talks/nips09npb.pdf
    27 Jan 2023: 21). Given s, the distribution of Z becomes:. p( Z | x , s, µ ( 1 : ) ) p( Z | x , µ ( 1 : ) ) 1µ I (0 s µ ) (24).

  9. Cambridge Machine Learning Group Publications

    https://mlg.eng.cam.ac.uk/pub/authors/
    13 Feb 2023: Publications, Machine Learning Group, Department of Engineering, Cambridge. current group:. [former members:. [by year:. [Tameem Adel. George Nicholson, Marta Blangiardo, Mark Briers, Peter J Diggle, Tor Erlend Fjelde, Hong Ge, Robert J B Goudie,

  10. Bayesian Classifier Combination Hyun-Chul Kim Zoubin GhahramaniKorea…

    https://mlg.eng.cam.ac.uk/pub/pdf/KimGha12.pdf
    13 Feb 2023: Bagging predictors. Ma-chine Learning 24, 123–140. Breiman, L., October 2001. Random forests. ... Vol. 24. pp. 791–798. Takács, G., Pilászy, I., Németh, B., Tikk, D., 2007.

  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.

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