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  2. 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,
  3. 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.
  4. 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.
  5. 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
  6. 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,
  7. 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
  8. 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.
  9. Nonparametric Transforms of Graph Kernelsfor Semi-Supervised Learning …

    https://mlg.eng.cam.ac.uk/zoubin/papers/ZhuKanGhaLaf04.pdf
    27 Jan 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
  10. 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
  11. Bayesian Sets Zoubin Ghahramani∗ and Katherine A. HellerGatsby…

    https://mlg.eng.cam.ac.uk/zoubin/papers/bsets-nips05.pdf
    27 Jan 2023: Behavioral and Brain. Sciences, 24:629–641.[6] Tong, S. (2005). Personal communication.

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