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21 - 30 of 45 search results for KaKaoTalk:ZA31 24 24 |u:mlg.eng.cam.ac.uk where 0 match all words and 45 match some words.

  1. Results that match 2 of 3 words

  2. Human Perceptions of Fairness in Algorithmic Decision Making: A Case…

    https://mlg.eng.cam.ac.uk/adrian/WWW18-HumanPerceptions.pdf
    19 Jun 2024: 47% 68% 70%B.S. 51% 32% 30%Liberal 57% 37% 33%Conservative 17% 24% 29%Moderate 21% 33% 34%Other 5% 6% 4%. ... Substance Abuse 4.84 0.08 0.07 0.10 0.24 0.07 0.68 0.26 0.22 0.20 0.07 0.284.

  3. Evaluating and Aggregating Feature-based Model Explanations

    https://mlg.eng.cam.ac.uk/adrian/IJCAI20_EvaluatingAndAggregating.pdf
    19 Jun 2024: µC(f, gSHAP) 1.94 0.26 1.36 0.36 2.33 0.23µC(f, gAVA) 1.93 0.24 1.24 0.32 2.61 0.29.

  4. Gauged Mini-Bucket Elimination for Approximate Inference Sungsoo Ahn…

    https://mlg.eng.cam.ac.uk/adrian/Gauge_for_Holder_Inference.pdf
    19 Jun 2024: We call these methods collectively Z-invariant methods. See [23, 24, 25] for discussions ofthe differences and relations between these methods. ... 24] G. David Forney Jr and Pascal O. Vontobel. Par-tition functions of normal factor graphs.

  5. The Geometry of Random Features Krzysztof Choromanski∗1 Mark…

    https://mlg.eng.cam.ac.uk/adrian/geometry.pdf
    19 Jun 2024: The Geometry of Random Features. Krzysztof Choromanski1 Mark Rowland2 Tamas Sarlos1 Vikas Sindhwani1 Richard E. Turner2 Adrian Weller231Google Brain, NY 2University of Cambridge, UK 3The Alan Turing Institute, UK. Abstract. We present an in-depth

  6. 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

  7. Blind Justice: Fairness with Encrypted Sensitive Attributes

    https://mlg.eng.cam.ac.uk/adrian/ICML18-BlindJustice.pdf
    19 Jun 2024: d features 51 62 7 24 23p sensitive attr. 1 1 7 1 1certification 802 ms 827 ms 288 ms 250 ms 765 mstraining 43 min 51 min 7 min 1 ... Bennett Capers, I. Blind justice. Yale Journal of Law &Humanities, 24:179, 2012.

  8. You Shouldn’t Trust Me: Learning Models WhichConceal Unfairness From…

    https://mlg.eng.cam.ac.uk/adrian/ECAI20-You_Shouldn%E2%80%99t_Trust_Me.pdf
    19 Jun 2024: mostimportant feature) in 2D reduced input space (scikit-learn [24]’s PCA imple-mentation). ... 4765–4774, (2017). [24] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B.

  9. One-network Adversarial Fairness

    https://mlg.eng.cam.ac.uk/adrian/AAAI2019_OneNetworkAdversarialFairness.pdf
    19 Jun 2024: log(1/δ). n(24). The term[4nI(x D0). 4nI(x D1). ]is what is estimated. ... From the latter note and (24), the two classifiers of theadversarial formulation proposed in (9) in the main docu-ment can be interpreted w.r.t.

  10. An Introduction to LP Relaxations for MAP Inference

    https://mlg.eng.cam.ac.uk/adrian/2018-MLSALT4-AW2-LP.pdf
    19 Jun 2024: x3. x4. x5. x6. s. balanced almost balanced(attractive up to flipping) 24 / 41.

  11. Leader Stochastic Gradient Descent for DistributedTraining of Deep…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS2019_LSGD_preprint.pdf
    19 Jun 2024: Landscape symmetries are commonin a plethora of non-convex problems [18, 19, 20, 21, 22], including deep learning [23, 24, 25, 26]. ... Understanding symmetries in deep networks. CoRR,abs/1511.01029, 2015. [24] A. Choromanska, M.

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