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1 - 50 of 54 search results for Economics test |u:mlg.eng.cam.ac.uk where 12 match all words and 42 match some words.
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  2. Discovering Interpretable Representations for Both Deep Generative…

    https://mlg.eng.cam.ac.uk/adrian/ICML18-Discovering.pdf
    19 Jun 2024: Significant re-sults are identified using a paired t-test with p = 0.05. ... The SVHN dataset contains 73,257training digits (instances) and 26,032 test digits.
  3. From Parity to Preference-based Notionsof Fairness in Classification…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-from-parity-to-preference.pdf
    19 Jun 2024: In this paper, we draw inspiration from the fair-division and envy-freeness literature in economics and game theory and proposepreference-based notions of fairness—given the choice between various sets ... Finally,we train the five classifiers
  4. Adrian Weller

    https://mlg.eng.cam.ac.uk/adrian/
    19 Jun 2024: Adrian serves on the boards of several organizations. He is a member of the World Economic Forum Global Future Council on the Future of AI, and is co-director of the ... Train and test tightness of LP relaxations in structured prediction.
  5. Transparency: Motivations and Challenges? Adrian…

    https://mlg.eng.cam.ac.uk/adrian/transparency.pdf
    19 Jun 2024: truth.”. Defining criteria and tests for practical faithfulness are important open pro-blems. ... 53. Prat, A.: The wrong kind of transparency. American Economic Review 95(3),862–877 (2005).
  6. A Unified Approach to Quantifying Algorithmic Unfairness: Measuring…

    https://mlg.eng.cam.ac.uk/adrian/KDD2018_inequality_indices.pdf
    19 Jun 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
  7. 19 Jun 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
  8. Human Perceptions of Fairness in Algorithmic Decision Making: A Case…

    https://mlg.eng.cam.ac.uk/adrian/WWW18-HumanPerceptions.pdf
    19 Jun 2024: We draw these latentproperties from the existing literature in social-economic-political-moral sciences, philosophy, and the law, as detailed below.I. ... To evaluate the model, we randomly split thedata into 50%/50% train/test folds five times, and
  9. Beyond Distributive Fairness in Algorithmic Decision Making: Feature…

    https://mlg.eng.cam.ac.uk/adrian/AAAI18-BeyondDistributiveFairness.pdf
    19 Jun 2024: 2011). For all reported results, we ran-domly split the data into 50%/50% train/test folds 5 times and re-port average statistics. ... In Univer-sity of Michigan Law & Economics Research Paper No. 16012.Ahmed, F.; Dickerson, J.
  10. Clamping Variables and Approximate Inference Adrian WellerColumbia…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS14-clamp.pdf
    19 Jun 2024: 6. Test models were constructed as follows: For n variables, singleton potentials were drawn θi U[Tmax,Tmax]; edge weights were drawn Wij U[0,Wmax] for attractive models, or Wij ... In UAI, 2009. P. Milgrom. The envelope theorems. Department of Economics
  11. Working Draft 1 Accountability of AI Under the Law: ...

    https://mlg.eng.cam.ac.uk/adrian/SSRN-id3064761-Dec19.pdf
    19 Jun 2024: Working Draft. 1. Accountability of AI Under the Law: The Role of Explanation. Finale Doshi-Velez, Mason Kortz, Ryan Budish, Chris Bavitz, Sam Gershman, David O’Brien, Kate Scott, Stuart Shieber, James Waldo, David Weinberger, Adrian Weller,.
  12. Orthogonal Estimation of Wasserstein Distances Mark Rowland∗1 Jiri…

    https://mlg.eng.cam.ac.uk/adrian/AISTATS19-slicedwasserstein.pdf
    19 Jun 2024: physics (Jordan et al., 1998) and economics(Galichon, 2016), and are increasingly used in machinelearning (Arjovsky et al., 2017; Gulrajani et al., 2017;Peyré and Cuturi, 2018). ... 5.1 Distance estimation. We begin with a test bed of small-scale
  13. Methods for Inference in Graphical Models

    https://mlg.eng.cam.ac.uk/adrian/phd_FINAL.pdf
    19 Jun 2024: 91. 7.6.2 Test sets. 93. 7.7 Conclusions. 95. 8 Clamping Variables and Approximate Inference 96. ... cave functions. They have attracted attention in combinatorics (Lovász, 1983), economics (Topkis,.
  14. Results that match 1 of 2 words

  15. The Voluntary International Carbon Alliance

    https://mlg.eng.cam.ac.uk/carl/climate/vica.html
    4 Jul 2024: Contextual background. Real progress on global warming requires a confluence of concepts, including from science, economics, sociology and ethics. ... The economic turnover relies on a single number, the price per ton of CO.
  16. https://mlg.eng.cam.ac.uk/index.xml

    https://mlg.eng.cam.ac.uk/index.xml
    3 Jul 2024: Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/ Cambridge Machine Learning Group Wowchemy (https://wowchemy.com) en-us Wed, 22 Mar 2023 00:00:00 0000
  17. When will we reach +1.5°C?

    https://mlg.eng.cam.ac.uk/carl/climate/tempvCO2.html
    4 Jul 2024: Here we are using the scatter plot to empirically test the strength of the relationship within the 65 years of CO.
  18. Who owns the atmosphere?

    https://mlg.eng.cam.ac.uk/carl/climate/eacc.html
    4 Jul 2024: Such a scheme would immediately put economic pressure on all users to reduce their utilisation of the common atmospheric resource. ... In the following years, low per capita emitters will gain immediate economic benefit from joining.
  19. Addressing Climate Change

    https://mlg.eng.cam.ac.uk/carl/climate/eaccs.html
    4 Jul 2024: Membership immediately creates economic pressure to cut emissions (for all members, not just large emitters).
  20. International Cooperation against Climate Change

    https://mlg.eng.cam.ac.uk/carl/climate/internationalcooperation.html
    4 Jul 2024: Strong individual economic pressures conflict with our common global interests. Only through global cooperation can individual and common incentives be re-aligned. ... This creates strong economic pressures to keep using fossil fuels. The real
  21. https://mlg.eng.cam.ac.uk/news/index.xml

    https://mlg.eng.cam.ac.uk/news/index.xml
    3 Jul 2024: Latest News | Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/news/ Latest News Wowchemy (https://wowchemy.com) en-us Wed, 22 Mar 2023 00:00:00 0000
  22. Ten papers from the group to appear at ICML 2016 | Cambridge Machine…

    https://mlg.eng.cam.ac.uk/news/ten-papers-from-the-group-to-appear-at-icml-2016/
    3 Jul 2024: Train and Test Tightness of LP Relaxations in Structured Prediction. Ofer Meshi, Mehrdad Mahdavi, Adrian Weller and David Sontag.
  23. TibGM: A Transferable and Information-Based Graphical Model Approach…

    https://mlg.eng.cam.ac.uk/adrian/ICML2019-TibGM.pdf
    19 Jun 2024: Confidence intervals are shown in all the plots. Unlessnoted otherwise, each experiment was repeated 50 timesand significance has been tested via a paired t-test with sig-nificance level at 5%. ... Significance is tested usingthe same paired t-test
  24. Seven new papers from the group to appear at NIPS 2015 in Montreal |…

    https://mlg.eng.cam.ac.uk/news/seven-new-papers-from-the-group-to-appear-at-nips-2015-in-montreal/
    3 Jul 2024: The list of papers are:. Statistical Model Criticism using Kernel Two Sample Tests.
  25. Bayesian Deep Learning via Subnetwork Inference · Cambridge MLG Blog

    https://mlg.eng.cam.ac.uk/blog/2021/07/21/subnetwork-inference.html
    12 Apr 2024: Figure 9: Results on the rotated MNIST benchmark, showing the mean $pm$ std of the test error (top) and log-likelihood (bottom) across three different seeds. ... methods. Figure 10: Results on the corrupted CIFAR-10 benchmark, showing the mean $pm$ std
  26. Speaking Truth to Climate Change

    https://mlg.eng.cam.ac.uk/carl/climate/truth.pdf
    25 Jun 2024: The effect of the alliance is to immediately apply strong economic pressure on allcontries to reduce emissions. ... Alliance dynamics. Initially, from a purely economic perspective, it’ll be advantageous for low percapita emitting countries to join
  27. 19 Jun 2024: Wolfe used for all runs, aftervalidating against smaller test set usingdual decomposition with guaranteed-approx mesh method (Weller andJebara, 2014).
  28. 19 Jun 2024: test. REFERENCES. B. Guenin. A characterization of weakly bipartite graphs. Journal of Combinatorial Theory, Series B, 83(1):112–168, 2001.
  29. Natural-Gradient Variational Inference 2: ImageNet-scale · Cambridge…

    https://mlg.eng.cam.ac.uk/blog/2021/11/24/ngvi-bnns-part-2.html
    12 Apr 2024: Reducing the prior precision $delta$ results in higher validation accuracy, but also a larger train-test gap, corresponding to more overfitting. ... Continual Learning: I personally think continual learning is a very good way to test approximate Bayesian
  30. Leader Stochastic Gradient Descent (LSGD) for Distributed Training of …

    https://mlg.eng.cam.ac.uk/adrian/LSGD_Poster_NeurIPS2019.pdf
    19 Jun 2024: Test error for the center variable versus wall-clock time. Figure: ResNet20 on CIFAR-10 with 4 workers (on the left) and 16 workers (on the right). ... Test error for the center variable versus wall-clock time. Figure: ResNet20 on CIFAR-10.
  31. ML-IRL: Machine Learning in Real Life Workshop at ICLR ...

    https://mlg.eng.cam.ac.uk/adrian/ML_IRL_2020-Counterfactual_Accuracy.pdf
    19 Jun 2024: would we have to give up so that the predictionfor the test point would change? ... 2017)), and then we constrain fora random test point to obtain counterfactual accuracy.
  32. Now You See Me (CME): Concept-based Model Extraction

    https://mlg.eng.cam.ac.uk/adrian/AIMLAI20-CME.pdf
    19 Jun 2024: For every𝑓 , we evaluated its fidelity and its task performance,using a held-out sample test set. ... 96.4 0.5%on a held-out test set (averaged over 5 runs).
  33. Orthogonal estimation of Wasserstein distances Mark Rowland*, Jiri…

    https://mlg.eng.cam.ac.uk/adrian/slicedwasserstein_poster.pdf
    19 Jun 2024: Naturally incorporate spatial information. • Applications from economics to machine learning.
  34. Evaluating and Aggregating Feature-based Model Explanations

    https://mlg.eng.cam.ac.uk/adrian/IJCAI20_EvaluatingAndAggregating.pdf
    19 Jun 2024: For Iris [Dua and Graff, 2017], we train our modelto 96% test accuracy. ... 45). Table 2: Faithfulness µF averaged over a test set: (Zero Baseline,Training Average Baseline).
  35. The Geometry of Random Features Krzysztof Choromanski∗1 Mark…

    https://mlg.eng.cam.ac.uk/adrian/geometry.pdf
    19 Jun 2024: pre-dictive distribution obtained by an exactly-trained GP, and(ii) predictive RMSE on test sets. ... Figure 8: Approximate GP regression results on Bostondataset. Reported numbers are average test RMSE, alongwith bootstrap estimates of standard error
  36. Leader Stochastic Gradient Descent for DistributedTraining of Deep…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS2019_LSGD_preprint.pdf
    19 Jun 2024: Test error for the center variableversus wall-clock time (original plot on the left and zoomed onthe right). ... Test loss is reported in Figure 13 in the Supplement. Finally, in Figure 6 we report theempirical results for ResNet50run on ImageNet.
  37. 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
  38. 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
  39. Bounding the Integrality Distance ofLP Relaxations for Structured…

    https://mlg.eng.cam.ac.uk/adrian/OPT2016_paper_3.pdf
    19 Jun 2024: Thus, the more training data we have, the better we can estimate theexpected integrality distance at test time.Remark 1. ... 9] O. Meshi, M. Mahdavi, A. Weller, and D. Sontag. Train and test tightness of LP relaxations instructured prediction.
  40. One-network Adversarial Fairness

    https://mlg.eng.cam.ac.uk/adrian/AAAI2019_OneNetworkAdversarialFairness.pdf
    19 Jun 2024: To test significance, we perform a paired t-test withsignificance level at 5%. ... Totest significance, we perform a paired t-test with significance level at 5%.
  41. 19 Jun 2024: Ex-periments are described in 6, where we examine test cases.Conclusions are discussed in 7. ... Given this performance, we used FW for all Bethe opti-mizations on the test cases.
  42. 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
  43. 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
  44. 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.
  45. 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
  46. 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.,
  47. 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
  48. 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
  49. 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.
  50. Ode to an ODE Krzysztof Choromanski ∗Robotics at Google ...

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS20-ODEtoODE.pdf
    19 Jun 2024: Table 1: Test accuracy comparison of different methods. Postfix terms refer to hidden depth for Dense,trigonometric polynomial degree for NANODE, and number of gates for HyperNet and ODEtoODE.
  51. Conditions Beyond Treewidth for Tightness of Higher-order LP…

    https://mlg.eng.cam.ac.uk/adrian/conditions.pdf
    19 Jun 2024: To detect if a graphis almost balanced, and if so then to find a distinguishedvertex, may be performed efficiently (simply hold out onevariable at a time and test the remainder to
  52. https://mlg.eng.cam.ac.uk/blog/feed.xml

    https://mlg.eng.cam.ac.uk/blog/feed.xml
    12 Apr 2024: Jekyll 2024-04-12T16:32:5900:00 https://mlg.eng.cam.ac.uk/blog/feed.xml MLG Blog Blog of the Machine Learning Group at the University of Cambridge An introduction to Flow Matching 2024-01-20T00:00:0000:00 2024-01-20T00:00:0000:00

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