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  2. Bayesian Monte Carlo Carl Edward RasmussenandZoubin GhahramaniGatsby…

    https://mlg.eng.cam.ac.uk/zoubin/papers/RasGha03.pdf
    27 Jan 2023: In detail, ifp(x) = N (b, B) and the Gaussian kernels on the data points areN (ai = x(i), A = diag(w21,. ,
  3. Prediction at an Uncertain Input for GaussianProcesses and Relevance…

    https://mlg.eng.cam.ac.uk/pub/pdf/QuiGirRas03.pdf
    13 Feb 2023: C = (Λ1 S1)1. cj = C(Λ1xj S. 1u) (32). 1N(a, A)N(b, B) N(c, C) with C = (A1 B1)1, c = C(A1a B1b) and normalizing constantzc = ... 2π)D/2|C|1/2|A|1/2|B|1/2 exp.
  4. Conditions Beyond Treewidth for Tightness of Higher-order LP…

    https://mlg.eng.cam.ac.uk/adrian/conditions.pdf
    19 Jun 2024: Let P ={x Rm|Ax b} be a polytope for some A =[a1,. ... ak]. > Rkm, b Rk (for some k N). Thenfor v Ext(P), we have.
  5. Scalable Gaussian Process Structured Prediction for Grid Factor Graph …

    https://mlg.eng.cam.ac.uk/pub/pdf/BraQuaNowGha14.pdf
    13 Feb 2023: b b b. b b b. b b. b ba1. a2. ... bb. b. b. ai. Figure 1. Left: Grid factor graph with a pairwise 4-connected fac-tor.
  6. Learning with Multiple Labels

    https://mlg.eng.cam.ac.uk/pub/pdf/JinGha02a.pdf
    13 Feb 2023: I p(y I x"B) B i I Si I YE S,. ... prediction p(y I x;, B). We will call this model 'EMPrior Model'.
  7. 27 Jan 2023: Ü Ø Þö øùú ì ùûD. Þ. üýeþgÿþgÿeþ CÿTþlýeþgÿÿ "!#$Tý%þ&' GÿlÿTþ(ÿ)&%"vÿTþ(,.-0/ÿvÿ (132546,Tý7!#3 ( 8qþ9:8;78qþ ( =<3 <>!9eÿþ 78;@8qþ( = A%þ(B!#BTýDCZþFE:!GH7IJJ% ... ªº O - ¤ b B» z ¤ £ x y z ¤ O £ x x y
  8. 27 Jan 2023: Ü Ø Þö øùú ì ùûD. Þ. üýeþgÿþgÿeþ CÿTþlýeþgÿÿ "!#$Tý%þ&' GÿlÿTþ(ÿ)&%"vÿTþ(,.-0/ÿvÿ (132546,Tý7!#3 ( 8qþ9:8;78qþ ( =<3 <>!9eÿþ 78;@8qþ( = A%þ(B!#BTýDCZþFE:!GH7IJJ% ... ªº O - ¤ b B» z ¤ £ x y z ¤ O £ x x y
  9. Adversarial Graph Embeddings for Fair Influence Maximization over…

    https://mlg.eng.cam.ac.uk/adrian/IJCAI20_AdversarialGraphEmbeddings.pdf
    19 Jun 2024: distributions of nodes from A and B in the embedding space(to have |UA||A|. ... Group AGroup BGroup AGroup B. (b) The fractions of influencednodes in the two groups.
  10. Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions

    https://mlg.eng.cam.ac.uk/pub/pdf/ZhuGhaLaf03a.pdf
    13 Feb 2023: T _ b: _ b T. T _ b. T _ b is the entropy of the field at the individual unlabeled datapoint b. ... The gradient is computed as [ W! VK X j. T _ b_ b: _ b [ W (12)where the values. _
  11. Gaussian Process

    https://mlg.eng.cam.ac.uk/teaching/4f13/1718/gaussian%20process.pdf
    19 Nov 2023: b. ],[A B. B> C. ])= p(x|y) = N(a BC1(y b), ABC1B>),. ... For Gaussians:. p(fn, f<n) = N([ a. b. ],[A B. B> C. ])=.

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