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  2. 4F13 Machine Learning: Coursework #3: Latent Dirichlet Allocation…

    https://mlg.eng.cam.ac.uk/teaching/4f13/1516/cw/coursework3.pdf
    19 Nov 2023: How manydocuments, how many words and how many unique words are there in A, in B and in the union of Aand B? ... Whatis the per-word perplexity over all documents in B? f) 10% : What would the perplexity be for a uniform multinomial?
  3. 27 Jan 2023: ä6-? <@ #, B D: àÊ @ # 26 D $ @ #, 26 D àÊ B <B à0à. ... û84åN<Bå 36ê è 84åëN-ò09<B3 9;54ëNå- è 84å-014êBåN<Hò09 è 36-05£54-3êBå 3ê è 84å> 9 è <H3 âè <Y954êBã:-êHå2952ì B B 36ê è 82å>
  4. 13 Feb 2023: ÐÑ Äê? ÐÑ 9<HQßÄÔõÇÉV ÿ ü åhýÿ ü åhý Z E6 _>@?ABXGRSBcN@Zu;,B]?AHïõê? ... q w,#]uÉC#],,}}v ,O k ,O ,O ¢ C,vÉí#XS,}}v < < S ,O qsÎSnStCÀq,} B < 1 n S B.
  5. Flexible Martingale Priors for Deep Hierarchies Jacob Steinhardt…

    https://mlg.eng.cam.ac.uk/pub/pdf/SteGha12.pdf
    13 Feb 2023: con-sisting of sets of the form US,a,b. We then claim thatC := {S | US,a,b B′} is the desired collection of mea-surable sets. ... Since D is Hausdorff, there exists someUS,a,b B′ such that p US,a,b and q 6 US,a,b, whichin particular implies that Pp[X
  6. LNAI 3176 - Unsupervised Learning

    https://mlg.eng.cam.ac.uk/pub/pdf/Gha03a.pdf
    13 Feb 2023: Sum-ming out C leads to P (A, B) = P (A)P (B). ... c P (C|A = a, B = a)),and continue this procedure until all variables are assigned values.
  7. Background material crib-sheet Iain Murray , October 2003 Here ...

    https://mlg.eng.cam.ac.uk/zoubin/ml06/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.
  8. 27 Jan 2023: C. B. D. E. Figure 1: Three kinds of probabilistic graphical model: undirected graphs, factor graphs and directed graphs. ... P (A, B, C, D, E) = c g1(A, C)g2(B, C, D)g3(C, D, E) (28).
  9. chaptertr.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/advmf.pdf
    27 Jan 2023: Q() is a produ t of Gamma densities Q(i) = G(i; a; bi)where a = a T2 , b = b 12gi, gi = PTt=1 y2ti Ui(diag() W 0)1U>i , ... J. Royal Statisti al So iety B, pages 157{224, 1988.[22 D.
  10. Practical Probabilistic Programming with Monads

    https://mlg.eng.cam.ac.uk/pub/pdf/SciGhaGor15.pdf
    13 Feb 2023: Specifically, consider the followingdesign. data PDist a whereReturn :: a -> PDist aPBind :: PDist b -> (b -> PDist a) -> PDist aPrimitive :: Sampleable d => d a -> PDist a. ... data CDist a wherePD :: PDist a -> CDist aCBind :: CDist b -> (b -> PDist a)
  11. (Multivariate) Gaussian (Normal) Probability Densities

    https://mlg.eng.cam.ac.uk/teaching/4f13/2324/gaussian%20and%20matrix%20equations.pdf
    19 Nov 2023: p(x, y) = N([ a. b. ],[A B. B> C. ])= p(x) = N(a, A),. ... b. ],[A B. B> C. ])= p(x|y) = N(a BC1(y b), ABC1B>),.
  12. paper.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/Gha01a.pdf
    13 Feb 2023: 7. ". &:. 1 "Q ". # ()! $. "Q " ' " ;.,< " %! #. %? &9? B? %. 4. " #. &? &? & ,. 5 1 -#? #? %& % &? $? % P & %P&. ... B< UA A- C DA+92+& ;#MM""" M/ MM92+&/< G D ( 0 4992.
  13. Gaussian Process

    https://mlg.eng.cam.ac.uk/teaching/4f13/2324/gaussian%20process.pdf
    19 Nov 2023: p(x, y) = p([ x. y. ])= N. ([ ab. ],[. A B. B> C. ]),. we get the marginal distribution of x, p(x) by. ... For Gaussians:. p(fn, f<n) = N([ a. b. ],[A B. B> C. ])=.
  14. 4F13 Machine Learning: Coursework #3: Latent Dirichlet Allocation…

    https://mlg.eng.cam.ac.uk/teaching/4f13/1213/cw/coursework3.pdf
    19 Nov 2023: How manydocuments, how many words and how many unique words are there in A, in B and in the union of Aand B? ... What is theper-word perplexity over all documents in B? f) 10% : What would the perplexity be for a uniform multinomial?
  15. 4F13: Machine Learning Lectures 1-2: Introduction to Machine Learning …

    https://mlg.eng.cam.ac.uk/zoubin/ml06/lect1-2.pdf
    27 Jan 2023: 1 θ = 1 and θ 0. Some distributions (cont). Uniform (x [a, b]):. ... p(x|a, b) ={. 1ba if a x b0 otherwise. Gamma (x 0):p(x|a, b) = b.
  16. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/0708/lect04.pdf
    19 Nov 2023: E(a) (b). Two types of nodes:• The circles in a factor graph. ... Z =aA. bB. cC. dD. eE. g1(A = a, C = c)g2(B = b, C = c, D = d)g3(C = c, D = d, E = e).
  17. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/1011/lect04.pdf
    19 Nov 2023: Z =aA. bB. cC. dD. eE. g1(A = a, C = c)g2(B = b, C = c, D = d)g3(C = c, D = d, E = e). ... A. D. C. B. E. A. D. C. B. E(a) (b) (c).
  18. - Machine Learning 4F13, Michaelmas 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1516/lect0304.pdf
    19 Nov 2023: p(x, y) = N([ a. b. ],[A B. B> C. ])= p(x) = N(a, A),. ... b. ],[A B. B> C. ])= p(x|y) = N(a BC1(y b), ABC1B>),.
  19. - Machine Learning 4F13, Spring 2014

    https://mlg.eng.cam.ac.uk/teaching/4f13/1314/lect0304.pdf
    19 Nov 2023: b. ],[A B. B> C. ])= p(x|y) = N(a BC1(y b), ABC1B>),. ... For Gaussians:. p(fi, f<i) = N([ a. b. ],[A B. B> C. ])=
  20. 3F3: Signal and Pattern Processing Lecture 1: Introduction to ...

    https://mlg.eng.cam.ac.uk/teaching/3f3/1011/lect1.pdf
    19 Nov 2023: Some distributions (cont). Uniform (x [a,b]):p(x|a,b) =. {1ba if a x b0 otherwise. ... Gamma (x 0):p(x|a,b) = b. a. Γ(a)xa1 exp{bx}. Beta (x [0, 1]):p(x|α,β) = Γ(α β).
  21. - Machine Learning 4F13, Spring 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1415/lect0304.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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