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g/linksets/9e77cfba-85c1-499b-ab4c-edbcdb6c5bb1","type":"application/linkset"},{"href":"https://eldorado.tu-dortmund.de/signposting/linksets/9e77cfba-85c1-499b-ab4c-edbcdb6c5bb1/json","type":"applicat [...] ribedby/9e77cfba-85c1-499b-ab4c-edbcdb6c5bb1","type":"application/vnd.datacite.datacite+xml"}],"anchor":"https://eldorado.tu-dortmund.de/items/9e77cfba-85c1-499b-ab4c-edbcdb6c5bb1","cite-as":[{"href": [...] .de/items/9e77cfba-85c1-499b-ab4c-edbcdb6c5bb1","type":"text/html"}],"linkset":[{"href":"https://eldorado.tu-dortmund.de/signposting/linksets/9e77cfba-85c1-499b-ab4c-edbcdb6c5bb1","type":"application/linkset"} …

Microsoft Word - Titelblatt Technical Report

Y20a + fV orl.−frei · Y20b + fPubl. · (X21a1 · Y22a1 +X21b1 · Y22b1 +X21c1 · Y22c1 +X21d1 · Y22d1 +X21e1 · Y22e1 +X21f1 · Y22f1 +X21g1 · Y22g1 +X21h1 · Y22h1 +X21a2 · Y22a2 +X21b2 · Y22b2 +X21c2 · Y22c2 [...] wie folgt bestimmt: 1. Ziehe α1 aus f(α1|y) 2. Ziehe λ1 aus f(λ1|α1,y) 3. Ziehe ỹ aus der Likelihood f(ỹ|α1,λ1) (s. Gleichung (2)) 4. Wiederhole Schitte 1 bis 3 m Mal. Die m Werte ỹ1,...,ỹm repräsentieren [...] Professorinnen 4,3 [1,0 , 8,1] 17,5 [5,0 , 31,9] 6,4 [0,3 , 14,5] 1,2 [0,0 , 4,0] Professoren 5,1 [1,1 , 9,8] 18,1 [4,6 , 34,1] 6,4 [0,2 , 14,8] 1,1 [0,0 , 4,3] 6.4.3 Prozentanteile Betrachtet man die Pro …

Distance Functions – Lecture Notes

y\right\rVert =1\) , this simplifies to: \[s_{\cos }(x,y) \underset {\scriptscriptstyle \left\lVert \mskip -1.5mux\mskip -1.5mu\right\rVert \mskip -1.5mu=\mskip -1.5mu\left\lVert \mskip -1.5muy\mskip -1.5mu\right\rVert [...] where \(o_1\) has 1 and \(o_2\) has 0 \(f_{00}\) = the number of attributes where \(o_1\) has 0 and \(o_2\) has 0 \(f_{11}\) = the number of attributes where \(o_1\) has 1 and \(o_2\) has 1 Simple matching [...] normalized: \(s(x,y)\in [0;1]\) and \(s(x,x)=1\) A distance \(\textup{dist}(x,y)\) implies a non-negative, symmetric, normalized similarity: \[s(x,y):= \frac{1}{1+\textup{dist}(x,y)} \in [0;1]\] If \(s(x,y)\) is …

Distance Functions – Lecture Notes

y\right\rVert =1\) , this simplifies to: \[s_{\cos }(x,y) \underset {\scriptscriptstyle \left\lVert \mskip -1.5mux\mskip -1.5mu\right\rVert \mskip -1.5mu=\mskip -1.5mu\left\lVert \mskip -1.5muy\mskip -1.5mu\right\rVert [...] where \(o_1\) has 1 and \(o_2\) has 0 \(f_{00}\) = the number of attributes where \(o_1\) has 0 and \(o_2\) has 0 \(f_{11}\) = the number of attributes where \(o_1\) has 1 and \(o_2\) has 1 Simple matching [...] normalized: \(s(x,y)\in [0;1]\) and \(s(x,x)=1\) A distance \(\textup{dist}(x,y)\) implies a non-negative, symmetric, normalized similarity: \[s(x,y):= \frac{1}{1+\textup{dist}(x,y)} \in [0;1]\] If \(s(x,y)\) is …

¯ S 1 ζ ¯ + S −K1 , K1 1−ζ ¯ < S ≤ K2 1−ζ ¯ α̃ ¯ (S −K2) +K2 −K1 , K2 1−ζ ¯ < S ≤ K2 1−ζ̄ max(˜̄αS 1 ζ̄ +K2, S)−K1 , K2 1−ζ̄ < S ≤ K2 K2 −K1 , S > K2 , α ¯ := −ζ ¯ ( 1−ζ ¯K1 ) 1−ζ ¯ζ ¯ , α̃ ¯ := 1− ( K2 [...] E [ C ∣∣∣Γ(τ1, X π(1) t,x (τ1), π(1)(τ1), ζ1)− Γ(τ1, X π(1) t,y (τ1), π(1)(τ1), ζ1) ∣∣∣k] ≤ E [ C ′ ∣∣∣Xπ(1) t,x (τ1)−Xπ(1) t,y (τ1) ∣∣∣k] ≤ C ′′|x− y|k, where C,C ′, C ′′ > 0 are constants and we have [...] ξ′∈Vn−1 J (π̂′,ξ′)(τ1, x̂ ′) ] ≥ inf τ1∈T ζ1∈Z∪{ζ0} Et,x [ Y π̂(n),(τ1;ζ1) + sup π′∈Un−1 inf ξ′∈Vn−1 J (π′,ξ′)(τ1, x̂ ′) ] − ε 2 ≥ inf τ1∈T ζ1∈Z∪{ζ0} sup π(n)∈U0 Et,x [ Y π(n),(τ1;ζ1) + v(n−1)(τ1, x ′) …

l̄∑ i=1 (f(xi)− yi)2 , r2 = ( l̄ ∑l̄ i=1 f(xi)yi − ∑l̄ i=1 f(xi) ∑l̄ i=1 yi )2( l̄ ∑l̄ i=1 f(xi)2 − (∑l̄ i=1 f(xi) )2 )( l̄ ∑l̄ i=1 y 2 i − (∑l̄ i=1 yi )2 ) . 3.2 A Simple Example of Running LIBSVM While [...] that yi ∈ {1,−1}, the primal optimization problem is min w,b,ξ,ρ 1 2 wTw − νρ+ 1 l l∑ i=1 ξi subject to yi(w Tφ(xi) + b) ≥ ρ− ξi, (4) ξi ≥ 0, i = 1, . . . , l, ρ ≥ 0. The dual problem is min α 1 2 αTQα subject [...] min α,α∗ 1 2 [ (α∗)T ,αT ] [ Q −Q −Q Q ] [ α∗ α ] + [ εeT − zT , εeT + zT ] [α∗ α ] subject to yT [ α∗ α ] = 0, 0 ≤ αt, α ∗ t ≤ C, t = 1, . . . , l, where y = [1, . . . , 1︸ ︷︷ ︸ l ,−1, . . . ,−1︸ ︷︷ ︸ l …

Evaluation-Sommer2022-anonymisiert

Sommer 2022: Seminare 1,00 2,00 3,00 4,00 5,00 6,00 1,00 1,50 2,00 2,50 3,00 3,50 4,00 4,50 5,00 5,50 6,00B ew er tu ng d er D oz en t* in ne n / de r B et re un g in sg es am t (1 = se hr g ut , . .., [...] Veranstaltung insgesamt (1=sehr gut, ..., 6=sehr schlecht) Evaluation Sommer 2022 1 2 3 4 5 6 1 2 3 4 5 6B ew er tu ng d er D oz en t* in ne n / de r B et re un g in sg es am t (1 = se hr g ut , . .., 6 [...] Veranstaltung insgesamt (1=sehr gut, ..., 6=sehr schlecht) Evaluation Sommer 2022: Vorlesungen 1 2 3 4 5 6 1 2 3 4 5 6B ew er tu ng d er D oz en t* in ne n / de r B et re un g in sg es am t (1 = se hr g ut , . …

Require: Array A[1..n] Ensure: Arrays nsv and psv 1: for i = 1 to n do 2: j ← i − 1 3: while j > 0∧A[j] > A[i ] do 4: nsv[j]← i 5: j ← psv[j] 6: psv[i ]← j 1 2 3 4 5 6 7 8 9 10 11 12 13 1 6 3 8 12 5 11 2 [...] Require: Array A[1..n] Ensure: Arrays nsv and psv 1: for i = 1 to n do 2: j ← i − 1 3: while j > 0∧A[j] > A[i ] do 4: nsv[j]← i 5: j ← psv[j] 6: psv[i ]← j 1 2 3 4 5 6 7 8 9 10 11 12 13 1 6 3 8 12 5 11 2 [...] Require: Array A[1..n] Ensure: Arrays nsv and psv 1: for i = 1 to n do 2: j ← i − 1 3: while j > 0∧A[j] > A[i ] do 4: nsv[j]← i 5: j ← psv[j] 6: psv[i ]← j 1 2 3 4 5 6 7 8 9 10 11 12 13 1 6 3 8 12 5 11 2 …