Search

Search Funnelback University

Search powered by Funnelback
61 - 70 of 279 search results for Economics test |u:mlg.eng.cam.ac.uk where 23 match all words and 256 match some words.
  1. Results that match 1 of 2 words

  2. Infinite Hidden Markov Models and extensions

    https://mlg.eng.cam.ac.uk/zoubin/talks/BayesHMMs10.pdf
    27 Jan 2023: IHMM evaluation in (Beal et al.,2002) is more elaborate: it allows the IHMM to con-tinue learning about new data encountered during test-ing. ... Subjecting theseresults to the same analysis as the artificial data re-veals similar compared test-set
  3. Variational Inference for the Indian Buffet Process Finale…

    https://mlg.eng.cam.ac.uk/pub/pdf/DosMilVanTeh09.pdf
    13 Feb 2023: Table 1: Running times in seconds and test log-likelihoods for the Yale Faces dataset. ... Algorithm K Time Test Log-Likelihood. 2 56 -0.7444Finite Gibbs 5 120 -0.4220.
  4. A Kernel Approach to Tractable Bayesian Nonparametrics

    https://mlg.eng.cam.ac.uk/pub/pdf/HusLac11.pdf
    13 Feb 2023: We foundthat kst outperformed both competing methods sig-nificantly (p < 0.01, two sample T-test). ... 3. As measureof performance, we used average confusion, i. e. thefraction of misclassified test images.
  5. Recent Advanced in Causal Modelling Using Directed Graphs

    https://mlg.eng.cam.ac.uk/zoubin/SALD/scheines.ppt
    27 Jan 2023: Can be applied to distributions where tests of conditional independence are known, but scores aren’t. ... 2) X1 - X2 into X2. Test. Test Conditions. X3. X2.
  6. PILCO: A Model-Based and Data-Efficient Approach to Policy Search

    https://mlg.eng.cam.ac.uk/pub/pdf/DeiRas11.pdf
    13 Feb 2023: 3)–(5). Doing this properlyrequires mapping uncertain test inputs through theGP dynamics model. ... b) Histogram (after 1,000 test runs)of the distances of the flywheel frombeing upright.
  7. 13 Feb 2023: Secondly, our empirical results (see Section 3)indicate, that the test set performance is simply not good. ... Table 1. Average log test densities over 10 random splits of the data.
  8. Prediction on Spike DataUsing Kernel Algorithms Jan Eichhorn, Andreas …

    https://mlg.eng.cam.ac.uk/pub/pdf/EicTolZieetal04.pdf
    13 Feb 2023: Finallywe train the best model on these four folds and compute an independent test error on theremaining fold. ... Table 1 Mean test error and standard error on the low contrast dataset.
  9. 13 Feb 2023: the test log-likelihood on a symmetric logscale as the discrepancy is very large. ... Test MSE on real-world regression problems (lower isbetter). 5.2. Approximation quality.
  10. 13 Feb 2023: Figure 8(a) shows test set log likelihoods for 10 ran-dom divisions of the data into training and test sets. ... test. dat. a. SFAAFA NS. FA. Fig 9. Test set log likelihoods on Prostate cancer dataset from Yu et al.
  11. Inferring a measure of physiological age frommultiple ageing related…

    https://mlg.eng.cam.ac.uk/pub/pdf/KnoParGlaWin11.pdf
    13 Feb 2023: Table 2: Hold out test. Values are log10(p) where p is the p-value for the Spearman rank correlationhypothesis test. ... The results are shown in Figure 2.2, where we are also able to include binary variables unlikefor the Spearman test.

Refine your results

Search history

Recently clicked results

Recently clicked results

Your click history is empty.

Recent searches

Recent searches

Your search history is empty.