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ML-IRL: Machine Learning in Real Life Workshop at ICLR ...
https://mlg.eng.cam.ac.uk/adrian/ML_IRL_2020-Counterfactual_Accuracy.pdf19 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. -
Now You See Me (CME): Concept-based Model Extraction
https://mlg.eng.cam.ac.uk/adrian/AIMLAI20-CME.pdf19 Jun 2024: For everyđť‘“ , 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). -
Orthogonal estimation of Wasserstein distances Mark Rowland*, Jiri…
https://mlg.eng.cam.ac.uk/adrian/slicedwasserstein_poster.pdf19 Jun 2024: Naturally incorporate spatial information. • Applications from economics to machine learning. -
Modelling data
https://mlg.eng.cam.ac.uk/teaching/4f13/2324/modelling%20data.pdf19 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. • -
Modelling data
https://mlg.eng.cam.ac.uk/teaching/4f13/2122/modelling%20data.pdf19 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. • -
- 4F13: Machine Learning
https://mlg.eng.cam.ac.uk/teaching/4f13/0708/lect06.pdf19 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. -
Bounding the Integrality Distance ofLP Relaxations for Structured…
https://mlg.eng.cam.ac.uk/adrian/OPT2016_paper_3.pdf19 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. -
4F13 Machine Learning: Coursework #4: Reinforcement Learning Zoubin…
https://mlg.eng.cam.ac.uk/teaching/4f13/1011/cw/coursework4.pdf19 Nov 2023: Test yourvalueIteration algorithm. -
Understanding the Bethe Approximation: When and How can it ...
https://mlg.eng.cam.ac.uk/adrian/abc.pdf19 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. -
4F13 Machine Learning: Coursework #1: Gaussian Processes Carl Edward…
https://mlg.eng.cam.ac.uk/teaching/4f13/1415/cw/coursework1.pdf19 Nov 2023: Show and comment on the fit and the hypers, and the predictions forthe test data.
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