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1 - 50 of 89 search results for Economics test |u:mlg.eng.cam.ac.uk where 12 match all words and 77 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. Speaking Truth to Climate Change

    https://mlg.eng.cam.ac.uk/carl/climate/truth.pdf
    4 Jul 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
  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. Mechanisms Against Climate Change

    https://mlg.eng.cam.ac.uk/carl/talks/cifar.pdf
    4 Jul 2024: The cooperative immediately creates strong economic pressure on all members to reduce emissions.
  27. 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.
  28. 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
  29. 19 Jun 2024: Wolfe used for all runs, aftervalidating against smaller test set usingdual decomposition with guaranteed-approx mesh method (Weller andJebara, 2014).
  30. 19 Jun 2024: test. REFERENCES. B. Guenin. A characterization of weakly bipartite graphs. Journal of Combinatorial Theory, Series B, 83(1):112–168, 2001.
  31. 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).
  32. 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.
  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. 4F13 Machine Learning: Coursework #3: Latent Dirichlet Allocation…

    https://mlg.eng.cam.ac.uk/teaching/4f13/2324/cw/coursework3.pdf
    19 Nov 2023: You may use the barh command. For thatmultinomial model, what is the highest and lowest possible test set log probability (for anypossible test set)? ... c) For the Bayesian model, what is the log probability for the test document with ID 2001?Explain
  35. 4F13 Machine Learning: Coursework #3: Latent Dirichlet Allocation…

    https://mlg.eng.cam.ac.uk/teaching/4f13/2122/cw/coursework3.pdf
    19 Nov 2023: c) For the Bayesian model, what is the log probability for the test document with ID 2001? ... Explainwhether, when computing the log probability of a test document, you would use the multinomial orthe categorical distribution function?
  36. Modelling data

    https://mlg.eng.cam.ac.uk/teaching/4f13/2122/modelling%20data.pdf
    19 Nov 2023: generalize from observations in the training set to new test cases(interpolation and extrapolation). • ... make predictions on test cases• interpret the trained model, what insights is the model providing?• evaluate the accuracy of model. •
  37. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/0708/lect06.pdf
    19 Nov 2023: Constraint-Based Learning: Use statistical tests of marginal and conditionalindependence. Find the set of DAGs whose d-separation relations match theresults of conditional independence tests.
  38. 4F13 Machine Learning: Coursework #4: Reinforcement Learning Zoubin…

    https://mlg.eng.cam.ac.uk/teaching/4f13/1011/cw/coursework4.pdf
    19 Nov 2023: Test yourvalueIteration algorithm.
  39. 4F13 Machine Learning: Coursework #1: Gaussian Processes Carl Edward…

    https://mlg.eng.cam.ac.uk/teaching/4f13/1314/cw/coursework1.pdf
    19 Nov 2023: Show and comment on the fit and the hypers, and the predictions forthe test data.
  40. - IB Paper 7: Probability and Statistics

    https://mlg.eng.cam.ac.uk/teaching/1BP7/1819/lect01.pdf
    19 Nov 2023: Why do we need this, is it useful?• Make inference about uncertain events• Form the basis of information theory• Test the strength of statistical evidence. •
  41. 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.,
  42. 3F3: Signal and Pattern Processing Lecture 1: Introduction to ...

    https://mlg.eng.cam.ac.uk/teaching/3f3/1011/lect1.pdf
    19 Nov 2023: Computational Neuroscience: neuronal networks, neural information processing,. • Economics: decision theory, game theory, operational research,.
  43. 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
  44. 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.
  45. Structured Prediction Models for Chord Transcription of Music Audio…

    https://mlg.eng.cam.ac.uk/adrian/icmla09adrian.pdf
    19 Jun 2024: Table 2 shows p-values for paired t-tests examining outperformance of each model compared to the baseline HMMv approach. ... Figure 2 shows the TOM test accuracies for all the models trained using Hamming distance as before.
  46. ML-IRL: Machine Learning in Real Life Workshop at ICLR ...

    https://mlg.eng.cam.ac.uk/adrian/ML_IRL_2020-CLUE.pdf
    19 Jun 2024: We evaluate the test set of fours, sevens, and nines with our BNN. ... This group was able to reach an accuracyof 88% on unseen test points.
  47. Exploring Properties of the Deep Image Prior Andreas…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS_2019_DIP7.pdf
    19 Jun 2024: To test the nature of these outputs we introduce a novel saliencymap approach, termed MIG-SG. ... To test this, we evaluated the sensitivity of DIP to changes innetwork architecture.
  48. - IB Paper 7: Probability and Statistics

    https://mlg.eng.cam.ac.uk/teaching/1BP7/1819/lect06.pdf
    19 Nov 2023: We get 10 people to blind test, each given a randomly selected drink. ... One-sided and two-sided tests. Depending on the circumstances, it may be necessary to use a two-sided test.
  49. Engineering Tripos Part IB SECOND YEAR PART IB Paper ...

    https://mlg.eng.cam.ac.uk/teaching/1BP7/1819/IBP7ex75.pdf
    19 Nov 2023: 7. Commercial airline pilots need to pass four out of five separate tests for certification. ... Assume that the testsare equally difficult, and that the performance on separate tests are independent.
  50. 4F13 Machine Learning: Coursework #3: Latent Dirichlet Allocation…

    https://mlg.eng.cam.ac.uk/teaching/4f13/1819/cw/coursework3.pdf
    19 Nov 2023: c) For the Bayesian model, what is the log probability for the test document with ID 2001? ... Explainwhether, when computing the log probability of a test document, you would use the multinomial withor without the “combinatorial factor”.
  51. Modelling data

    https://mlg.eng.cam.ac.uk/teaching/4f13/1819/modelling%20data.pdf
    19 Nov 2023: generalize from observations in the training set to new test cases(interpolation and extrapolation). • ... make predictions on test cases• interpret the trained model, what insights is the model providing?• evaluate the accuracy of model. •
  52. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/0809/lect06.pdf
    19 Nov 2023: Constraint-Based Learning: Use statistical tests of marginal and conditionalindependence. Find the set of DAGs whose d-separation relations match theresults of conditional independence tests.

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