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21 - 30 of 55 search results for Economics test |u:mlg.eng.cam.ac.uk where 12 match all words and 43 match some words.

  1. Results that match 1 of 2 words

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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).

  9. 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.

  10. 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

  11. 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).

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