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paper.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/KimGha08.pdf13 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. -
Bayesian Hierarchical Clustering Katherine A. Heller…
https://mlg.eng.cam.ac.uk/zoubin/papers/icml05heller.pdf27 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. -
grasshopper.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/GolZhuVanAnd07.pdf13 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. -
LNCS 5342 - Outlier Robust Gaussian Process Classification
https://mlg.eng.cam.ac.uk/pub/pdf/KimGha08a.pdf13 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. -
newroyftp.dvi
https://mlg.eng.cam.ac.uk/zoubin/papers/RGBN.pdf27 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. -
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, -
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, -
Time-Sensitive Dirichlet Process Mixture Models Xiaojin Zhu Zoubin…
https://mlg.eng.cam.ac.uk/zoubin/papers/tdpmTR.pdf27 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 -
Bayesian Knowledge Corroboration with LogicalRules and User Feedback…
https://mlg.eng.cam.ac.uk/pub/pdf/KasVanGraHer10.pdf13 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. -
1 Robust Filtering and Smoothing with Gaussian Processes Marc ...
https://mlg.eng.cam.ac.uk/pub/pdf/DeiTurHubetal12.pdf13 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
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