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  2. 4F13 Probabilistic Machine Learning: Coursework #1: Gaussian…

    https://mlg.eng.cam.ac.uk/teaching/4f13/2324/cw/coursework1.pdf
    19 Nov 2023: having to deal with constrained op-timization for positive parameters), but you will want to report them in their natural domain.
  3. Beyond Distributive Fairness in Algorithmic Decision Making: Feature…

    https://mlg.eng.cam.ac.uk/adrian/AAAI18-BeyondDistributiveFairness.pdf
    19 Jun 2024: We provide fast submodular mechanisms to op-timize the tradeoff between procedural fairness and predic-tion accuracy. ... Rather, we sometimes see a sig-nificant change in the whole feature set used, in order to op-timize the objective.
  4. 19 Jun 2024: See 5.1 in the Appendix for further analysis. 6 EXPERIMENTS. We are interested in the empirical performance of the op-timum Bethe marginals and partition function, as the re-. ... Results on the validation set are shown in Figure 4, indi-cating that FW
  5. C:/Users/Adrian/Documents/GitHub/betheClean/docs/nb-UAI.dvi

    https://mlg.eng.cam.ac.uk/adrian/nb-UAI.pdf
    19 Jun 2024: accuracy) of ageneralbinarypairwise MRF. Runtime is practical forsmall real-world problems. • This now allows the accuracy of the global Bethe op-timum to be tested. • ... Importantly, we now have the opportunity to ex-amine rigorously the
  6. An Introduction to LP Relaxations for MAP Inference

    https://mlg.eng.cam.ac.uk/adrian/2018-MLSALT4-AW2-LP.pdf
    19 Jun 2024: The rationalefor using an approximate solver is that especially in the beginning of the op-timization process the current relaxation is not a “tight” relaxation of the cutpolytope anyway.”.
  7. TibGM: A Transferable and Information-Based Graphical Model Approach…

    https://mlg.eng.cam.ac.uk/adrian/ICML2019-TibGM.pdf
    19 Jun 2024: Kappen, H. Path integrals and symmetry breaking for op-timal control theory.
  8. Orthogonal Estimation of Wasserstein Distances Mark Rowland∗1 Jiri…

    https://mlg.eng.cam.ac.uk/adrian/AISTATS19-slicedwasserstein.pdf
    19 Jun 2024: Genevay, A., Cuturi, M., Peyré, G., and Bach, F.(2016). Stochastic Optimization for Large-scale Op-timal Transport. ... 2018). Computational Op-timal Transport. arXiv. Pitié, F., Kokaram, A. C., and Dahyot, R.
  9. Structured Evolution with Compact Architectures for Scalable Policy…

    https://mlg.eng.cam.ac.uk/adrian/structured_icml_full.pdf
    19 Jun 2024: Ourexperiments include a detailed comparison of variousDFO schemes on a collection of 212 benchmark op-timization problems from (Moré & Wild, 2009) and12 continuous control tasks from the OpenAI Gymbenchmark suite. •
  10. Discovering Interpretable Representations for Both Deep Generative…

    https://mlg.eng.cam.ac.uk/adrian/ICML18-Discovering.pdf
    19 Jun 2024: Also, note that an interpretable model will op-timize the dependence between the latent space z and theside information s to express a simple, i.e.
  11. One-network Adversarial Fairness

    https://mlg.eng.cam.ac.uk/adrian/AAAI2019_OneNetworkAdversarialFairness.pdf
    19 Jun 2024: classifier, we make onlyslight adjustments to the architecture including adding a newhidden layer, in order to enable the concurrent adversarial op-timization for fairness and accuracy.

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