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51 - 60 of 261 search results for katalk:PC53 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. Factored Contextual Policy Search with Bayesian Optimization Robert…

    https://mlg.eng.cam.ac.uk/pub/pdf/PinKarKupetal19.pdf
    13 Feb 2023: For the Gym tasks, weemploy an extension [24] of the DMP framework [12] toefficiently generate goal-directed trajectories. ... 16, no. 5, pp. 1190–1208, 1995. [24] J. Kober, K. Mülling, O.

  3. Beyond Dataset Bias: Multi-task UnalignedShared Knowledge Transfer…

    https://mlg.eng.cam.ac.uk/pub/pdf/TomQuaCapLam12.pdf
    13 Feb 2023: 15 85.38 3.42 80.66 2.12MSRCORID 45.80 4.26 51.79 2.73 52.59 2.93 40.24 3.11. ... In:. NIPS. (2010)24. Leen, G.: Context assisted information extraction. PhD thesis, University of the.

  4. Variational Inference for Nonparametric Multiple Clustering Yue Guan, …

    https://mlg.eng.cam.ac.uk/pub/pdf/GuaDyNiuetal10.pdf
    13 Feb 2023: The first 100 eigenvectors retains a total of 99.24% ofthe overall variance. ... Journalon Machine Learning Research, 3:583–617, 2002. [24] M. Turk and A.

  5. Augmented Attribute Representations Viktoriia Sharmanska1, Novi…

    https://mlg.eng.cam.ac.uk/pub/pdf/ShaQuaLam12.pdf
    13 Feb 2023: There are 50 animals classesin this dataset. The dataset also contains semantic information in the form of an85-dimensional Osherson’s [24] attribute vector for each animal class. ... In: CVPR. (2010) 3027–3034. 24. Osherson, D.N., Stern, J., Wilkie,

  6. Split and Merge EM Algorithm for Improving Gaussian Mixture Density…

    https://mlg.eng.cam.ac.uk/pub/pdf/UedNakGha00b.pdf
    13 Feb 2023: Table 1. Log-likelihood/sample size. Initial value EM DAEM SMEM. Training. Mean 159.1 148.2 147.9 145.1Std 1.77 0.24 0.04 0.08.

  7. Gender Classification with Bayesian Kernel Methods [IJCNN1261]

    https://mlg.eng.cam.ac.uk/pub/pdf/KimKimGha06b.pdf
    13 Feb 2023: 24, no. 5, pp. 707–711, 2002. [6] A. Jain and J.

  8. Tree-Structured Stick Breaking for Hierarchical Data Ryan Prescott…

    https://mlg.eng.cam.ac.uk/pub/pdf/AdaGhaJor10.pdf
    13 Feb 2023: To efficiently learn thenode parameters, we used Hamiltonian (hybrid) Monte Carlo (HMC) [24], taking 25 leapfrog HMCsteps, with a randomized step size. ... 24] Radford M. Neal. MCMC using Hamiltonian dynamics. In Handbook of Markov chain Monte

  9. 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.

  10. 89 Probabilistic Models for Incomplete Multi-dimensional Arrays Wei…

    https://mlg.eng.cam.ac.uk/pub/pdf/ChuGha09.pdf
    13 Feb 2023: 0897 1.0720 0.0855Sugar process 7 268 571 4 0.3323 0.0010 0.3303 0.0009 0.2242 0.0009Dorrit 27 551 24 5 0.5556 0.0075 ... In this experimentwith about 2.24 million training points, it took about0.5 hour to complete 100 iterations of the EM algo-rithm on

  11. Cambridge Machine Learning Group Publications

    https://mlg.eng.cam.ac.uk/pub/
    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,

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