TU Dortmund -- Computer Science VIII

subgradient descent (4: stochastic subgradient method) > Reading: Nemirovski et al., Robust Stochastic Approximation Approach to Stochastic Programming, SIOPT 2009 Sections 1~2.2, 4~5 (inclusive) Lecture [...] 3: Conjugation and dual problems Lecture 26 (28.1): Duality 4: Dual of Lasso and Fused Lasso Lecture 27 (2.2): Conic Program 1 Lecture 28 (4.2): Conic Program 2 Intro to Julia Extra material: Optimality [...] Attendance to practices (Übung) is REQUIRED. Office Hour (lecturer): Thursday 13:00-14:00, LS8, OH 12, Raum 4.023 (or by appointments) Content: This course focuses on optimization techniques to find solutions of …

. Time τ µ- w av e La se r ! !" !"" !""" Decay time / µs Si gn al Hahn echo 2 pulses 4 8 16 32 64 128 256 Figure 4: Refocusing of electron spin coherence by spin-echo experiments. The curves in the lower [...] the probability to detect a second photon immediately after the first drops to zero for short times [4]. This is easy to understand by considering that after the emission of a photon, the center is in the [...] C ~S~IkC , where the sum runs over all sites occupied by 13C iso- topes. Frequency shift / MHz 0 2 4 6 8 Frequency / GHz 0 1 2 3 En er gy 2.87 GHz 14N 13C Figure 3: Spectrum from a single N/V center showing …

On Theory of Informational Functions Presence

=∗ ∫ ℜ −++ +∗= ⎥⎦ ⎤ ⎢⎣ ⎡ 2 ~,ˆˆˆˆ 2 1 ˆˆˆˆ 2 1~, dxAxxAxx ωαββααββαω (21) ( ) ( ) 2 ~,ˆˆˆˆ~, 4 12 ~,ˆˆˆˆ~, 4 1 ∫ ℜ ∗− +∗+∫ ℜ ∗+ +∗= dxAxxAxxdxAxxAxx ωαββαωωαββαω Missed member is equal to 0, because αα [...] const. (3 ) expression is equal of information function at cx presentation: cAcxcxAxxF ~,~,ˆ ∗=∗ ωω (4) where cA~ is canonically conjugate fuzzy subset: ( ) ( ) =∗ ∫ ℘ +∗=℘ cdxcAcxcx cI cAcxcxc ~;~; ωω ωωχ [...] d icAxxc ~;~;ˆ ∗−=∗℘ ωω (8) And analogically cAcxcx cdx d iccAcxcx ~;~;ˆ ∗=∗℘ ωω (9) Note that by (4),(5) and (2),(1*): dxAxxcAxxx ~;ˆ~; ∗℘∫ ℜ +∗=∗ ωωω (10) cdxcAcxcx c Acxcxcx ~;ˆ~; ∗℘∫ ℜ +∗=∗ ωωω (11) …

Ver ¨ anderliche Sterne 4 2.1 Kriterien zur Einteilung . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Verwendung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 Das LSST . . . . . [...] . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.4 Auswertung der aufgenommenen Daten . . . . . . . . . . . . . . 5 3 Maschinelles Lernen 7 4 Entscheidungsb ¨ aume 7 5 Random Forests 8 5.1 Wahl des [...] astronomy. Significance, 9(4):22–25, August 2012. [8] Gary L. Grunkemeier and YingXing Wu. Bootstrap resampling methods: something for nothing? The Annals of Thoracic Surgery, 77(4):1142–1144, July 2004. [9] …

µM 10000 µM 0 0 0 2 2 2 2 2 2 GBC glibenclamide 1 µM 4 µM 20 µM 2 2 2 2 2 2 2 2 2 GF griseofulvin 1 µM 4 µM 20 µM 2 2 2 2 2 2 2 2 2 GFZ gemfibrozil 4 µM 20 µM 100 µM 2 2 2 2 2 2 2 2 2 HCB hexachlorobenzene [...] 2 CCL4 carbon tetrachloride 300 µM 1500 µM 7500 µM 2 2 2 2 2 2 2 2 2 CFB clofibrate 12 µM 60 µM 300 µM 2 2 2 2 2 2 2 2 2 CHL chlorpheniramine NA NA 18 µM 90 µM 0 0 0 0 2 2 0 2 2 CHX cycloheximide 4 µM 20 [...] 30 µM 150 µM 0 0 0 0 2 2 0 2 2 DIS disopyramide NA NA 700 µM 3500 µM 0 0 0 0 2 2 0 2 2 DNP 2,4-dinitrophenol 4 µM 20 µM 100 µM 0 0 0 2 2 2 2 2 2 DNZ danazol NA NA 7 µM 35 µM 0 0 0 0 2 2 0 2 2 DOX doxorubicin …

Samples were obtained from 3-4 independent experiments; for each experiment 5 different concentrations plus untreated controls were tested. Each sample was measured in 2-4 technical replicates. Relative [...] V160_4 APAP C3 200 µM 16.57209 16.141214 25.420511 25.223951 22.85974 23.048023 25.685928 25.743784 31.047295 31.165178 25.747606 25.926323 28.768297 29.169724 29.587902 29.156141 V160_5 APAP C4 1 mM 16 [...] V161_4 APAP C3 200 µM 16.493568 16.376917 27.245045 27.57991 30.860802 30.731556 26.648903 26.340467 36.136192 35.74881 26.905987 27.350151 28.964426 29.382427 31.013407 31.257998 V161_5 APAP C4 1 mM 16 …

2.61* 4.08 Female 2.56 4.20** Male 2.79 3.95** Research University 2.54** 4.04 University of Applied Sciences 2.86** 4.03 Disciplines Engineering, Natural Sciences 2.80 3.81** Humanities 2.52 4.18 Medicine [...] 568 19.07 209 42.3 Lecturers and assistants 3520 1.41 7 1.4 Scientific staff 188,047 75.37 85 17.2 Teachers for special tasks 10,351 4.15 96 19.4 Honorary staff – – 78 15.8 Total 249,486 100 494 100 Humanities [...] university faculty from research universities. 4.3 Measurement 4.3.1 Dependent variables The dependent variables in our study are intrinsic motivation (M 4.0) and extrinsic motivation (M 2.7), each of which …

Financial Crisis -1,4 -9,5 9,0 0,6 -1,5 1,9 0,8 0,0 0,8 -0,20 -0,60 -1,60 -4,70 0,20 0,60 0,70 0,80 2,30 -10,0 -8,0 -6,0 -4,0 -2,0 0,0 2,0 4,0 6,0 8,0 10,0 Start of the crisis Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Ch an [...] . . . . 17 1.4 Data and methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.4.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.4.2 Methodology [...] . . . . . . 80 3.4.1 Data and Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 3.4.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 3.4.3 Descriptive Statistics …

Microsoft Word - Slice_050809.doc

layer j: 1- )(,1 xO iAi µ= i =1 ,2 2- )( 2,1 xO iBi − = µ i=3,4 3- 2,1,1,2 +×= iii OOO i=1,2 4- 2,21,2 ,2 ,3 OO O O i i + = i=1,2 5- )(,3,3,4 iiiiiii rxqxpOfOO ++== i=1,2 6- ∑= iOO ,41,5 The membership function [...] parameters for layer 1 and 4. Gra- dient decent are typically used for non lin- ear parameters of layer 1 while batch or recursive least squares are used for linear parameters of layer 4 or even combination of [...] ANFIS σ =1.5 Epoch 150 0.8606 0.9331 0.9523 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 LM GRNN RBF LVQ ANFIS Dataset1 Dataset2 Dataset3 Figure 4: The classification rate for each dataset by using five neural …