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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

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.

19 Jun 2024: D. Schlesinger and B. Flach. Transforming an arbitrary minsumproblem into a binary one. ... a,b B = {0,1}.Note that a third ‘dimension’ restricted to the value 1 has been added for notational convenience.

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

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.

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)

27 Jan 2023: 6ûý 3. 68òBð¡ñ1ðEþ)ú¡ÿ,ÆðJõú¡ïxð1òÃújúùóÐÐóÆÐðlú:jóøWÐûA 3. 6jûòBð!Æÿ,Æðô =. bdc (û/A3! -. 6 m x #"!3!$I6 "!3 O$I6 %B&%53'$ 6bdc3 (û/A3! -.

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.

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).

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. ])=.

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.

19 Nov 2023: How many documents, how many words and how many unique words are there inA, in B and in the union of A and B? ... What is the per-wordperplexity? What is the per-word perplexity over all documents in B?

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?

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?

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>),.

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.

19 Nov 2023: N(x|a, A) N(P> x|b, B) = zc N(x|c, C). • is proportional to a Gaussian density function with covariance and mean. ... 1(b P> a). )Ghahramani Lecture 1 and 2: Probabilistic Regression 38 / 38.

19 Jun 2024: Z. (b). X. Y. Z. 12 / 26. D-separation (“directed separation”) in Bayesian networks. ... over A,B,C :. p(D) =a,b,c. p(A = a,B = b,C = c,D). 28 / 26.

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.

19 Nov 2023: p(x, y) = N([ a. b. ],[A B. B> C. ])= p(x|y) = N(aBC1(yb), ABC1B>),. ... b. ],[A B. B> C. ])= p(x|y) = N(aBC1(yb), ABC1B>). Do try this at home!