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LNAI 7524 - Modelling Input Varying Correlations between Multiple…
https://mlg.eng.cam.ac.uk/pub/pdf/WilGha12a.pdf13 Feb 2023: modeling through spatially varying coregionalization. Test 13(2), 263–312 (2004)Gouriéroux, C.: ARCH models and financial applications. ... The Re-. view of Economic Studies 61(2), 247–264 (1994)Murray, I., Adams, R.P., MacKay, D.J.: Elliptical -
Variational Inference for BayesianMixtures of Factor Analysers Zoubin …
https://mlg.eng.cam.ac.uk/zoubin/papers/nips99.pdf27 Jan 2023: Thick lines are accepted attempts, thin lines arerejected attempts. (middle) Exp 3: Means of the factor loading matrices. ... The variational Bayesian approachcorrectly inferred both the number of Gaussians and their intrinsic dimensionalities(Figure 3, -
The Case for Process Fairness in Learning:Feature Selection for ...
https://mlg.eng.cam.ac.uk/adrian/grgic.pdf16 May 2024: 3. Prior literature in social, economic, legal, and political sciences distinguishing between directdiscrimination and indirect discrimination makes similar observations as we do in this paper. ... For each of the classifiers, we also compute -
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring…
https://mlg.eng.cam.ac.uk/adrian/KDD2018_inequality_indices.pdf16 May 2024: In this paper, we propose to quantify unfairness using inequal-ity indices that have been extensively studied in economics andsocial welfare [3, 10, 19]. ... For all experiments, we repeatedly split the data into 70%-30%train-test sets 10 times and -
PILCO: A Model-Based and Data-Efficient Approach to Policy Search
https://mlg.eng.cam.ac.uk/pub/pdf/DeiRas11.pdf13 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. -
Gaussian Process Change Point Models
https://mlg.eng.cam.ac.uk/pub/pdf/SaaTurRas10.pdf13 Feb 2023: Weevaluated the models’ ability to predict next day snow-fall using 35 years of test data. ... Method Negative Log Likelihood p-value MSE p-valueNile Data (200 Training Points, 462 Test Points). -
Bayesian Structured Prediction using Gaussian Processes Sébastien…
https://mlg.eng.cam.ac.uk/pub/pdf/BraQuaGha14a.pdf13 Feb 2023: For each session, we use 10 videosto train a chain CRF or GPstruct and the rest as test data. ... f MAP scheme, thinning at1:1 000. middle: Effect of thinning, i.e. -
Variational Inferen e for BayesianMixtures of Fa tor AnalysersZoubin…
https://mlg.eng.cam.ac.uk/pub/pdf/GhaBea99a.pdf13 Feb 2023: We used the dataset of 800 data pointsfrom a shrinking spiral from [12 as another test of how well the algorithm ould. ... The variational Bayesian approa h orre tly inferred both the number of Gaussians and their intrinsi dimensionalities(Figure 3, -
Learning to Parse Images
https://mlg.eng.cam.ac.uk/pub/pdf/HinGhaTeh99a.pdf13 Feb 2023: Then the learning. 2,3. 2,4. 2,5. 3,4. 3,5. 4,5. Figure 1: Sample images from the test set. ... The 64 middle layer units are meantto encode low level features, while each of the 4 top level units are meant to encodea digit class. -
544 The Block Diagonal Infinite Hidden Markov Model Thomas ...
https://mlg.eng.cam.ac.uk/pub/pdf/SteGhaGoretal09.pdf13 Feb 2023: Each dataset had 2000 stepsof training data and 2000 steps of test data. ... these were not significantly different (two sam-ple t-test, p = 0.3).
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