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61 - 80 of 261 search results for katalk: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. 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,

  3. images/test_user_webdesign.eps

    https://mlg.eng.cam.ac.uk/pub/pdf/IwaShaGha13a.pdf
    13 Feb 2023: We estimate the Dirichlet parameter β by using the fixed-point iteration method described in [24]. ... γW. EnX. n′=1. αun exp(γtn)! , (24). where W () is the Lambert W function, which solves theequation x = W (x) exp(W (x)), and.

  4. 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.

  5. Prediction at an Uncertain Input for GaussianProcesses and Relevance…

    https://mlg.eng.cam.ac.uk/pub/pdf/QuiGirRas03.pdf
    13 Feb 2023: Ex[σ2(x)] varx(µ(x. )) (24). where Ex indicates the expectation under x.

  6. 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.

  7. Nonparametric Bayesian Sparse Factor Models with application to Gene…

    https://mlg.eng.cam.ac.uk/pub/pdf/KnoGha11b.pdf
    13 Feb 2023: 14 15 16 17 18 19 20 21 22 23 24 25 26 270. ... 2004) (N = 24,D = 100,3000 MCMC iterations). 5.3. Biological data: E.

  8. Student-t Processes as Alternatives to Gaussian Processes Amar Shah…

    https://mlg.eng.cam.ac.uk/pub/pdf/ShaWilGha14a.pdf
    13 Feb 2023: 40. 20. 0. 20. Function Evaluation. Max. FunctionValue. GPTP. 1. 4 8 12 16 20 24 28 32 36 400. ... 5. 10. 15. 20. Function Evaluation. Min. FunctionValue. GPTP. 1. 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30.

  9. Graph-based Semi-supervised Learning Zoubin Ghahramani Department of…

    https://mlg.eng.cam.ac.uk/zoubin/talks/lect3ssl.pdf
    27 Jan 2023: Background Extraction. date 10/24 11/13 1/6 1/14 1/20 1/21 1/271 128 193 153 4742 256 193 4483 288 305 5934 204 190 3945 266

  10. Latent-Space Variational Bayes Jaemo Sung, Student Member,…

    https://mlg.eng.cam.ac.uk/pub/pdf/SunGhaBan08.pdf
    13 Feb 2023: 4 MIXTURE OF GAUSSIANS. Finite mixture [23], [24] is a latent variable model which provides a. ... been used to demonstrate inference algorithms inthe pattern recognition, statistics, and machine learning literatures[6], [24], [25], [26].

  11. 368 A kernel method for unsupervised structured network inference ...

    https://mlg.eng.cam.ac.uk/pub/pdf/LipSteGhaetal09.pdf
    13 Feb 2023: The Countries data set contains in-formation on 24 countries, comprising 4 numeric at-tributes: population size, the GNP per capita, theaverage education level (as expressed by scalars), aswell as energy ... Countries trade data (24 nodes)population size

  12. Predictive Automatic Relevance Determinationby Expectation…

    https://mlg.eng.cam.ac.uk/zoubin/papers/Qi04.pdf
    27 Jan 2023: PredictiveARDEPPredictiveProbARDEP. EvidenceARDEPAllFeaturesEPlinear. SVMQP_RegAdaBoostLP_RegAdaBoost. AdaBoost_RegAdaBoost. RBF. 23.5 24.5 25.5 26.5. Test error rate.

  13. Predictive Automatic Relevance Determinationby Expectation…

    https://mlg.eng.cam.ac.uk/pub/pdf/QiMinPic04a.pdf
    13 Feb 2023: PredictiveARDEPPredictiveProbARDEP. EvidenceARDEPAllFeaturesEPlinear. SVMQP_RegAdaBoostLP_RegAdaBoost. AdaBoost_RegAdaBoost. RBF. 23.5 24.5 25.5 26.5. Test error rate.

  14. Accelerated Sampling for the Indian Buffet Process Finale Doshi-Velez …

    https://mlg.eng.cam.ac.uk/pub/pdf/DosGha09.pdf
    13 Feb 2023: 24.557 -13.977 -26.936. The running times and quality criteria are summarisedin table 2.

  15. Marc P. Deisenroth, Jan Peters, and Carl E. Rasmussen: ...

    https://mlg.eng.cam.ac.uk/pub/pdf/DeiPetRas08.pdf
    13 Feb 2023: 578 2.0108 9.23 6.2105 9.81012 9.02488 1.2108 9.24 3.1105 1.31012 9.05.

  16. Gaussian Process Change Point Models

    https://mlg.eng.cam.ac.uk/pub/pdf/SaaTurRas10.pdf
    13 Feb 2023: In FinancialTimes. April 24 2009. Li, D. X. On default correlation: A copula function ap-proach.

  17. Accelerated sampling for the Indian Buffet Process

    https://mlg.eng.cam.ac.uk/pub/pdf/DosGha09a.pdf
    13 Feb 2023: 24.557 -13.977 -26.936. The running times and quality criteria are summarisedin table 2.

  18. Bayesian Learning in Undirected Graphical Models:Approximate MCMC…

    https://mlg.eng.cam.ac.uk/pub/pdf/MurGha04a.pdf
    13 Feb 2023: Pattern Recogni-tion Letters, 24:1251–1259, 2003. [19] David Edwards and Tomáš Havránek.

  19. LNAI 8189 - Variational Hidden Conditional Random Fields with Coupled …

    https://mlg.eng.cam.ac.uk/pub/pdf/BouZafMor13a.pdf
    13 Feb 2023: L(q) = 〈log F(y, x, π′, X)p(π′)〉q(y,s,π′|X) 〈log q(y, s|X)q(π′)〉q(y,s,π′|X)(24). Since log ... IEEE Trans. Neural Networks andLearning Systems 24(1), 170–177 (2013). 8. Ghahramani, Z., Beal, M.: Propagation Algorithms for

  20. Relational Learning with Gaussian Processes Wei ChuCCLS Columbia…

    https://mlg.eng.cam.ac.uk/pub/pdf/ChuSinGhaetal07.pdf
    13 Feb 2023: 28. 26. 24. 22. 20. 18. κ. log P(E). log P(E,Y).

  21. Relational Learning with Gaussian Processes Wei ChuCCLS Columbia…

    https://mlg.eng.cam.ac.uk/zoubin/papers/relationalgp.pdf
    27 Jan 2023: 28. 26. 24. 22. 20. 18. κ. log P(E). log P(E,Y).

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