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1 - 10 of 44 search results for KaKaoTalk:ZA31 24 24 |u:mlg.eng.cam.ac.uk where 0 match all words and 44 match some words.

  1. Results that match 2 of 3 words

  2. Posts by Tag · Cambridge MLG Blog

    https://mlg.eng.cam.ac.uk/blog/posts-by-tag
    12 Apr 2024: Bayesian Inference. 24 November 2021. Natural-Gradient Variational Inference 2: ImageNet-scale. By Siddharth Swaroop. ... Deep Learning. 24 November 2021. Natural-Gradient Variational Inference 2: ImageNet-scale. By Siddharth Swaroop.

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

    https://mlg.eng.cam.ac.uk/adrian/pabc.pdf
    19 Jun 2024: 100. Maximum coupling strength y. BethelocalBethecycleBethemargTRWlocalTRWcycleTRWmarg. log partition error. 2 8 16 24 320. ... 2 8 16 24 320. 0.1. 0.2. 0.3. 0.4. Maximum coupling strength y.

  4. Cambridge MLG Blog

    https://mlg.eng.cam.ac.uk/blog/
    12 Apr 2024: 24 November 2021. Natural-Gradient Variational Inference 2: ImageNet-scale. By Siddharth Swaroop.

  5. Blind Justice: Fairness with Encrypted Sensitive Attributes

    https://mlg.eng.cam.ac.uk/adrian/poster_ICML18_BlindJustice.pdf
    19 Jun 2024: Bank. Datasets and Feasibility. Adult Bank COMPAS German SQFn training examples 214 215 212 29 216d features 51 62 7 24 23p sensitive attributes 1 1 7 1 1certification 802 ms

  6. Clamping Variables and Approximate Inference

    https://mlg.eng.cam.ac.uk/adrian/slides_msr2.pdf
    19 Jun 2024: 24 / 21. Error in log Z vs number of clamps: complete graphs. ... 24 / 21. Time (secs) vs error in log Z for various methods.

  7. Clamping Variables and Approximate Inference

    https://mlg.eng.cam.ac.uk/adrian/newsclamp.pdf
    19 Jun 2024: 0.1. 0.2. 0.3. 0.4. max interaction strength W 24 / 19.

  8. 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: Published on 24 November 2021. This is the blog of the Cambridge Machine Learning Group.

  9. Revisiting the Limits of MAP Inference by MWSS on Perfect Graphs

    https://mlg.eng.cam.ac.uk/adrian/slides-revisit.pdf
    19 Jun 2024: Revisiting the Limits of MAP Inference by MWSSon Perfect Graphs. Adrian WellerUniversity of Cambridge. CP 2015Cork, Ireland. Slides and full paper athttp://mlg.eng.cam.ac.uk/adrian/. 1 / 21. Motivation: undirected graphical models (MRFs). •

  10. The Case for Process Fairness in Learning:Feature Selection for ...

    https://mlg.eng.cam.ac.uk/adrian/grgic.pdf
    19 Jun 2024: Age 46% 56% 32%Gender 24% 50% 22%Race 24% 35% 15%. Table 3: Comparing judgment of fairness of each feature, of 54 male users, when they have differentknowledge about the ... Age 42% 63% 33%Gender 24% 54% 23%Race 18% 43% 18%. Table 5: Comparing judgment

  11. Junction Tree, BP and Variational Methods

    https://mlg.eng.cam.ac.uk/adrian/2018-MLSALT4-AW3-approx.pdf
    19 Jun 2024: 24 / 32. The log-partition function log Z. Since D(q‖p) 0, we have. ... a finite convex hull 3. M(G) = conv {φ(e), e X m} (5.24).

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