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  1. Fully-matching results

  2. 13 Feb 2023: a) (b) (c)-2 µ 2-2 µ 2-2 µ 2. 0. v. ... a) Independent Normal and inverseGamma, N (µ|µµ, vµ)IG(v|a, b). b) Normal-inverse-Gamma,N (µ|µµ, vµv)IG(v|a, b).
  3. 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,. ,
  4. 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.
  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. 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. _
  10. 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. ])=.
  11. Background material crib-sheet Iain Murray , October 2003 Here ...

    https://mlg.eng.cam.ac.uk/zoubin/course03/cribsheet.pdf
    27 Jan 2023: P (A = a|B = b) is the probability A = a occurs given the knowledge B = b. ... Note. a P (A = a, B = b|H) =. P (B = b|H) gives the normalising constant of proportionality.
  12. Cambridge Machine Learning Group Publications

    https://mlg.eng.cam.ac.uk/pub/authors/
    13 Feb 2023: by year:. [Tameem Adel. George Nicholson, Marta Blangiardo, Mark Briers, Peter J Diggle, Tor Erlend Fjelde, Hong Ge, Robert J B Goudie, Radka Jersakova, Ruairidh E King, Brieuc C L Lehmann, ... J. von Kügelgen, A.-H. Karimi, U. Bhatt, I. Valera, A.
  13. 13 Feb 2023: L. Gresele, J. von Kügelgen, J. M. Kübler, E. Kirschbaum, B. ... J. von Kügelgen, A.-H. Karimi, U. Bhatt, I. Valera, A. Weller, and B.
  14. Blind Justice: Fairness with Encrypted Sensitive Attributes

    https://mlg.eng.cam.ac.uk/adrian/ICML18-BlindJustice.pdf
    19 Jun 2024: Wethen multiply the sum by b/n > 2m. As long as b, b/n(and thus also n/b) can be represented with sufficient preci-sion, which is the case in ... Details about parameters and thealgorithm can be found in Section B in the appendix.
  15. /users/joe/src/tops/dvips

    https://mlg.eng.cam.ac.uk/pub/pdf/UedNakGha00a.pdf
    13 Feb 2023: Typically, b = 8 or b = 16 is employed. Each block is regarded as ad(= bb)-dimensional vector x. ... J. R. Statist. Soc. B, 59(4), 731–792. Sugiyama, Y., & Ariki, Y.
  16. gf2gp.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/gf2gp.pdf
    27 Jan 2023: vNm4y=Zvx|¥zkkzpwMv¥zBkZz}BkvNtpkMp8emvwvxmzzkZB|kuB'kumkvzy=wDpw yQvzkum wDpwp k kVBNp Mv kumvzMkzp wDpw BkMpz Bv zkkB|kumBkzpmZkvxV}kv8tpZºA@.B B Pµumk B ªºmvxMwDpwzpmZkvx}BkvNtpkºµkuVkx|vxmvxkevxmM}m|vNmpwDDp ... D 0.
  17. Bayesian Knowledge Corroboration with LogicalRules and User Feedback…

    https://mlg.eng.cam.ac.uk/pub/pdf/KasVanGraHer10.pdf
    13 Feb 2023: B., Santos, L. L.,Matsumoto, S.: A First-Order Bayesian Tool for Probabilistic Ontologies. ... AAAI Press (2008). 30. Frey, B. J., Mackay, D. J. C.: A Revolution: Belief Propagation in Graphs withCycles.
  18. On the Convergence of Bound Optimization Algorithms Ruslan…

    https://mlg.eng.cam.ac.uk/pub/pdf/SalRowGha03a.pdf
    13 Feb 2023: A. A. B. B. 0 50 100 150 200 250 300. ... ihoo. d. Con. st. Logistic Regression. A. B, C. 0 5 10 15 20 250.
  19. 19 Jun 2024: Partition thevariable indices into two subsets, A [n] = {1,. ,n}and B = [n] A. ... Proof B. We provide an alternative derivation which essen-tially incorporates the flipping into the proof.
  20. psb04.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/DubHwaRan04a.pdf
    13 Feb 2023: A tX ¿Î;BgªQµ|XXºJ X D«OVirª"µrXÀiiD e@ ) B b_µrªiDj_«_|«OXº_µr ªeµrX ß««_0;«OjiDªµDiÀXirÑ e@!Xr 8 /ªQµ|XD3 a«_#e«O;_µ;«_jªc_ ¿ Ì ... 81È»µr|O_e«_'X;¿B«_»_B&«_B_#XD«ªr_e«_DÀXº{_µrG6ÑH1IÒOÃjrDª@;É_µ"_µ
  21. Machine Learning Group Publications

    https://mlg.eng.cam.ac.uk/pub/topics/
    13 Feb 2023: Henry B. Moss, Sebastian W. Ober, and Victor Picheny.

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