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  2. Clamping Improves TRW and Mean Field Approximations Adrian Weller∗ ...

    https://mlg.eng.cam.ac.uk/adrian/clamp_aistats_final.pdf
    16 May 2024: Journal of Automated Reasoning, 24(1-2):225–275, 2000. N. Ruozzi. The Bethe partition function of log-supermodular graphical models.
  3. 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
    16 May 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.
  4. From Parity to Preference-based Notionsof Fairness in Classification…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-from-parity-to-preference.pdf
    16 May 2024: decisionoutcomes. A number of learning mechanisms have been proposed to achieve parity in treatment [24],. ... Angwin. https://github.com/propublica/compas-analysis, 2016. [24] B. T. Luong, S. Ruggieri, and F.
  5. Methods for Inference in Graphical Models

    https://mlg.eng.cam.ac.uk/adrian/phd_FINAL.pdf
    16 May 2024: 3 Additional Background 24. 3.1 MAP Inference and Tractable Cases. 24.
  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/poster_ICML18_BlindJustice.pdf
    16 May 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
  8. Clamping Variables and Approximate Inference

    https://mlg.eng.cam.ac.uk/adrian/newsclamp.pdf
    16 May 2024: 0.1. 0.2. 0.3. 0.4. max interaction strength W 24 / 19.
  9. Revisiting the Limits of MAP Inference by MWSS on Perfect Graphs

    https://mlg.eng.cam.ac.uk/adrian/slides-revisit.pdf
    16 May 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 Unreasonable Effectiveness of StructuredRandom Orthogonal…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-unreasonable-effectiveness.pdf
    16 May 2024: sin2(φ) cos2(ϕ1) cos2(ϕ2) sin2(ϕ1)cos2(ϕ2) sin. 2(ϕ1) sin2(φ) cos2(ϕ1). (24). This observation greatly simplifies the integral from Equation (22) involving the term

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