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1 - 10 of 12 search results for KaKaoTalk:po03 op |u:mlg.eng.cam.ac.uk where 0 match all words and 12 match some words.

  1. Results that match 1 of 2 words

  2. Beyond Distributive Fairness in Algorithmic Decision Making: Feature…

    https://mlg.eng.cam.ac.uk/adrian/AAAI18-BeyondDistributiveFairness.pdf
    16 May 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.

  3. Understanding the Bethe Approximation: When and How can it ...

    https://mlg.eng.cam.ac.uk/adrian/abc.pdf
    16 May 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

  4. C:/Users/Adrian/Documents/GitHub/betheClean/docs/nb-UAI.dvi

    https://mlg.eng.cam.ac.uk/adrian/nb-UAI.pdf
    16 May 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

  5. An Introduction to LP Relaxations for MAP Inference

    https://mlg.eng.cam.ac.uk/adrian/2018-MLSALT4-AW2-LP.pdf
    16 May 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.”.

  6. Orthogonal Estimation of Wasserstein Distances Mark Rowland∗1 Jiri…

    https://mlg.eng.cam.ac.uk/adrian/AISTATS19-slicedwasserstein.pdf
    16 May 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.

  7. TibGM: A Transferable and Information-Based Graphical Model Approach…

    https://mlg.eng.cam.ac.uk/adrian/ICML2019-TibGM.pdf
    16 May 2024: Kappen, H. Path integrals and symmetry breaking for op-timal control theory.

  8. Structured Evolution with Compact Architectures for Scalable Policy…

    https://mlg.eng.cam.ac.uk/adrian/structured_icml_full.pdf
    16 May 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. •

  9. Discovering Interpretable Representations for Both Deep Generative…

    https://mlg.eng.cam.ac.uk/adrian/ICML18-Discovering.pdf
    16 May 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.

  10. One-network Adversarial Fairness

    https://mlg.eng.cam.ac.uk/adrian/AAAI2019_OneNetworkAdversarialFairness.pdf
    16 May 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.

  11. Bethe and Related Pairwise Entropy Approximations Adrian…

    https://mlg.eng.cam.ac.uk/adrian/Weller_UAI15_BetheAndRelated.pdf
    16 May 2024: ReferencesF. Bach. Learning with submodular functions: A convex op-. timization perspective.

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