Introduction Snippets Conclusion References Beamer snippets J´ er´ emie DECOCK October 21, 2014 Decock Beamer snippets
Introduction Snippets Conclusion References
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Jeremie DECOCK
October 21, 2014
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Introduction
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Introduction
TODOTODO
TODO
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Basic frameSubtitle
. . .
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Citations and referencescite, label and ref commands
Eq. (1) define the Bellman equation [Bel57]
V (x) = maxa∈Γ(x)
{F (x , a) + βV (T (x , a))} (1)
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Listsitemize, enumerate and description commands
I item 1
I item 2
I . . .
1. item 1
2. item 2
3. . . .
First item 1
Second item 2
Last . . .
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Colorscolor environment
small
footnotesize
scriptsize
tiny
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Fonts colorcolor environment
Red Green Blue
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Centered imageincludegraphics command
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Subfiguresfigure, subfigure and includegraphics commands
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Blocksblock command
Block 1Blablabla
Block 2Blablabla
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Equations
V (x) = maxa∈Γ(x)
{F (x , a) + βV (T (x , a))}
V (x) = maxa∈Γ(x)
{F (x , a) + βV (T (x , a))}
V (x) = maxa∈Γ(x)
{F (x , a) + βV (T (x , a))} (2)
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Equation arrayeqnarray command
Expectation of N =n∑
i=1
E(Zi )
=n∑
i=1
γ
dβ/2
c(d)β
iαβ
=γ
dβ/2c(d)β
n∑i=1
1
iαβ
= z
Variance of N =n∑
i=1
V (Zi ) (3)
≤n∑
i=1
E(Zi ) (as V (Zi ) ≤ E(Zi )) (4)
≤ z
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Matrices
Am,n =
a1,1 a1,2 · · · a1,n
a2,1 a2,2 · · · a2,n
......
. . ....
am,1 am,2 · · · am,n
M =
56
16 0
56 0 1
6
0 56
16
M =
( x y
A 1 0B 0 1
)
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Systems of equation array
f (n) =
{n/2 if n is even−(n + 1)/2 if n is odd
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Mathematical programmingwith align
max z = 4x1 + 7x2
s.t. 3x1 + 5x2 ≤ 6 (5)
x1 + 2x2 ≤ 8 (6)
x1, x2 ≥ 0
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Mathematical programmingwith alignat
Max z = x1 + 12x2
s.t. 13x1 + x2 + 12x3 ≤ 5
x1 + x3 ≤ 16
15x1 + x2 = 14
xj ≥ 0, j = 1, 2, 3.
Max z = x1 + 12x2
s.t. 13x1 + x2 + 12x3 ≤ 5 (7)
x1 + x3 ≤ 16 (8)
15x1 + x2 = 14 (9)
xj ≥ 0, j = 1, 2, 3.
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Animations
Slide 1
I . . .
I . . .
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Animations
Slide 2
I . . .
I . . .
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Animations
Slide 3
I . . .
I . . .
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Algorithmsalgorithmic command
Require:〈S,A,T ,R〉, an MDPγ, the discount factorε, the maximum error allowed in the utility of any state in an iteration
Local variables:U,U′, vector of utilities for states in S, initially zeroδ, the maximum change in the utility of any state in an iteration
repeatU ← U′
δ ← 0for all s ∈ S do
U′[s]← R[s] + γmaxa∑
s′ T (s, a, s′)U[s′]if |U′[s]− U[s]| > δ thenδ ← |U′[s]− U[s]|
end ifend for
until δ < ε(1− γ)/γreturn U
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Verbatim
To insert a verbatim paragraph, the frame have to be declared”fragile”. The title has to be written in frametitle command, notas argument of frame (I don’t know why. . . ).
.--.
|o_o |
|:_/ |
// \ \
(| | )
/’\_ _/‘\
\___)=(___/
# gcc -o hello hello.c
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Listings I
1 #!/usr/bin/env python
2 # -*- coding: utf -8 -*-
3
4 # Author: Jeremie Decock
5
6 def main():
7 """ Main function """
8
9 print "Hello world!"
10
11 if __name__ == ’__main__ ’:
12 main()
listings/test.py
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Tabletabular command
γ = 1 (small noise) γ < 1 (large noise)Proved rate for R-EDA 1
β ≤ α1
2β ≤ αFormer lower bounds α ≤ 1 α ≤ 1R-EDA experimental rates α = 1
β α = 12β
Rate by active learning α = 12 α = 1
2
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Multi-columnscolumns and column commands
Blablabla
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URL
http://www.jdhp.org/
JDHP
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Conclusion
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Conclusion
TODOTODO
TODO
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References I
Richard Ernest Bellman, Dynamic programming, PrincetonUniversity Press, Princeton, New Jersey, USA, 1957.
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