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41 - 50 of 54 search results for Economics test |u:mlg.eng.cam.ac.uk where 12 match all words and 42 match some words.
  1. Results that match 1 of 2 words

  2. What Keeps a Bayesian Awake At Night? Part 2: Night Time · Cambridge…

    https://mlg.eng.cam.ac.uk/blog/2021/03/31/what-keeps-a-bayesian-awake-at-night-part-2.html
    12 Apr 2024: Practitioners should also test the hell out of their inference schemes to gain confidence in them. ... The acid test is whether your inference scheme works on the real world data you care about, so test cases also need to replicate aspects of this
  3. What Keeps a Bayesian Awake At Night? Part 1: Day Time · Cambridge…

    https://mlg.eng.cam.ac.uk/blog/2021/03/31/what-keeps-a-bayesian-awake-at-night-part-1.html
    12 Apr 2024: Examples include inferring the mass of the Higgs boson ($X$) from collider data ($D$); estimating the prevalence of Covid 19 infections ($X$) from PCR test data ($D$); or reconstructing files ($X$) ... One way to view them is as unit tests that the
  4. 2018 Formatting Instructions for Authors Using LaTeX

    https://mlg.eng.cam.ac.uk/adrian/AIES18-crowd_signals.pdf
    19 Jun 2024: For training our classifiers, we use 5-fold cross-validation.In each test, the original sample is partitioned into 5 sub-samples, out of which 4 are used as training data, ... The processis then repeated 5 times, with each of the 5 sub-samplesused
  5. Blind Justice: Fairness with Encrypted Sensitive Attributes

    https://mlg.eng.cam.ac.uk/adrian/ICML18-BlindJustice.pdf
    19 Jun 2024: Figure 2 shows the test set accuracyover the constraint value. By design, the synthetic datasetexhibits a clear trade-off between accuracy and fairness. ... Biddle, D. Adverse impact and test validation: A practi-tioner’s guide to valid and defensible
  6. Geometrically Coupled Monte Carlo Sampling Mark Rowland∗University of …

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS18-gcmc.pdf
    19 Jun 2024: 5.2 Variance-reduced ELBO estimation for deep generative models. In this section, we test GCMC sampling strategies on a deep generative modelling application. ... 10. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, and
  7. You Shouldn’t Trust Me: Learning Models WhichConceal Unfairness From…

    https://mlg.eng.cam.ac.uk/adrian/ECAI20-You_Shouldn%E2%80%99t_Trust_Me.pdf
    19 Jun 2024: Each histogramrepresents the ranking across the test set assigned by the designated feature importance method. ... These results suggest that ourattack is successful in generalising across unseen test points.
  8. Unifying Orthogonal Monte Carlo Methods

    https://mlg.eng.cam.ac.uk/adrian/ICML2019-unified.pdf
    19 Jun 2024: 3, 4. Approximating kernel matrices: We test the relative er-ror of kernel matrix estimation for the above estimators forthe Gaussian kernel (following the setting of Choromanski& Sindhwani, 2016). ... A kernel two-sample test. J. Mach. Learn.Res.,
  9. 19 Jun 2024: Tightness of LP Relaxations for Almost Balanced Models. Adrian Weller Mark Rowland David SontagUniversity of Cambridge University of Cambridge New York University. Abstract. Linear programming (LP) relaxations are widelyused to attempt to identify a
  10. THIS VERSION FIXES A TYPO IN THE STATEMENT OF ...

    https://mlg.eng.cam.ac.uk/adrian/Weller15_revisit_fixed.pdf
    19 Jun 2024: We shall first prove sufficiency then necessity of the condi-tion. In order to test whether a derived NMRF is perfect, weuse Theorem 1, hence must check for possible odd holes
  11. Structured Evolution with Compact Architectures for Scalable Policy…

    https://mlg.eng.cam.ac.uk/adrian/structured_icml_full.pdf
    19 Jun 2024: Monte Carlo gradient estimators. We test all three vari-ants of the Monte Carlo gradient estimator discussed in thepaper, namely: antithetic ES, forward finite-difference ESand vanilla ES.

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