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# Page 2 Lecture Notes in Computer Science 4475 Commenced ...

Page 2 Lecture Notes in Computer Science 4475 Commenced ...

## Page 2 Lecture Notes in Computer Science 4475 Commenced

• Page 2 and 3: Lecture Notes in Computer Science 4
• Page 4 and 5: Volume Editors Pierluigi Crescenzi
• Page 6 and 7: Program Chairs Conference Organizat
• Page 10 and 11: On Embedding a Graph in the Grid wi
• Page 12 and 13: On Embedding a Graph in the Grid wi
• Page 14 and 15: On Embedding a Graph in the Grid wi
• Page 16 and 17: On Embedding a Graph in the Grid wi
• Page 18 and 19: On Embedding a Graph in the Grid wi
• Page 20 and 21: On Embedding a Graph in the Grid wi
• Page 22 and 23: On Embedding a Graph in the Grid wi
• Page 24 and 25: Fun with Sub-linear Time Algorithms
• Page 26 and 27: Wooden Geometric Puzzles: Design an
• Page 28 and 29: Wooden Geometric Puzzles: Design an
• Page 30 and 31: length N − 1 Wooden Geometric Puz
• Page 32 and 33: nG 4 nG nG Wooden Geometric Puzzles
• Page 34 and 35: Wooden Geometric Puzzles: Design an
• Page 36 and 37: Wooden Geometric Puzzles: Design an
• Page 38 and 39: Wooden Geometric Puzzles: Design an
• Page 40 and 41: HIROIMONO Is NP-Complete 31 We will
• Page 42 and 43: C1 C2 C3 C4 HIROIMONO Is NP-Complet
• Page 44 and 45: if t(xi) =⊤ if t(xi) =⊥ Rsc HIR
• Page 46 and 47: HIROIMONO Is NP-Complete 37 - There
• Page 48 and 49: HIROIMONO Is NP-Complete 39 Peter B
• Page 50 and 51: Tablatures for Stringed Instruments
• Page 52 and 53:

Tablatures for Stringed Instruments

• Page 54 and 55:

Tablatures for Stringed Instruments

• Page 56 and 57:

Tablatures for Stringed Instruments

• Page 58 and 59:

E B G D A E Tablatures for Stringed

• Page 60 and 61:

C C♯ Tablatures for Stringed Inst

• Page 62 and 63:

Knitting for Fun: A Recursive Sweat

• Page 64 and 65:

Knitting for Fun: A Recursive Sweat

• Page 66 and 67:

Knitting for Fun: A Recursive Sweat

• Page 68 and 69:

Knitting for Fun: A Recursive Sweat

• Page 70 and 71:

Knitting for Fun: A Recursive Sweat

• Page 72 and 73:

Knitting for Fun: A Recursive Sweat

• Page 74 and 75:

7 Concluding Remarks Knitting for F

• Page 76 and 77:

Pictures from Mongolia 67 this pape

• Page 78 and 79:

Pictures from Mongolia 69 elements

• Page 80 and 81:

4 Small-Width Posets Pictures from

• Page 82 and 83:

log n−1 � i=log n−⌊log w⌋

• Page 84 and 85:

Algorithm 3. An algorithm for good

• Page 86 and 87:

Pictures from Mongolia 77 Note that

• Page 88 and 89:

Efficient Algorithms for the Spoone

• Page 90 and 91:

Efficient Algorithms for the Spoone

• Page 92 and 93:

Efficient Algorithms for the Spoone

• Page 94 and 95:

4 An Improved Algorithm Efficient A

• Page 96 and 97:

Efficient Algorithms for the Spoone

• Page 98 and 99:

Efficient Algorithms for the Spoone

• Page 100 and 101:

Efficient Algorithms for the Spoone

• Page 102 and 103:

High Spies (or How to Win a Program

• Page 104 and 105:

2 Problem Model High Spies (or How

• Page 106 and 107:

High Spies (or How to Win a Program

• Page 108 and 109:

High Spies (or How to Win a Program

• Page 110 and 111:

High Spies (or How to Win a Program

• Page 112 and 113:

❦ c(i1,j) ✻c(j, i1) ❦✛c(j,

• Page 114 and 115:

High Spies (or How to Win a Program

• Page 116 and 117:

6 Concluding Remarks High Spies (or

• Page 118 and 119:

Robots and Demons (The Code of the

• Page 120 and 121:

Robots and Demons (The Code of the

• Page 122 and 123:

Robots and Demons (The Code of the

• Page 124 and 125:

Robots and Demons (The Code of the

• Page 126 and 127:

4.2 Gathering Problem Robots and De

• Page 128 and 129:

Robots and Demons (The Code of the

• Page 130 and 131:

The Traveling Beams Optical Solutio

• Page 132 and 133:

The Traveling Beams Optical Solutio

• Page 134 and 135:

The Traveling Beams Optical Solutio

• Page 136 and 137:

The Traveling Beams Optical Solutio

• Page 138 and 139:

The Traveling Beams Optical Solutio

• Page 140 and 141:

The Traveling Beams Optical Solutio

• Page 142 and 143:

e 2 V2 e5 V 1 V 3 e 6 e1 =(v1 ,v2 )

• Page 144 and 145:

The Worst Page-Replacement Policy

• Page 146 and 147:

The Worst Page-Replacement Policy 1

• Page 148 and 149:

The Worst Page-Replacement Policy 1

• Page 150 and 151:

The Worst Page-Replacement Policy 1

• Page 152 and 153:

The Worst Page-Replacement Policy 1

• Page 154 and 155:

The Worst Page-Replacement Policy 1

• Page 156 and 157:

y ′ y ′′ z Fig. 1. Cutting of

• Page 158 and 159:

Die Another Day 149 In Section 4 we

• Page 160 and 161:

Die Another Day 151 infinite subseq

• Page 162 and 163:

Die Another Day 153 given by the le

• Page 164 and 165:

Die Another Day 155 20. Leadbetter,

• Page 166 and 167:

Approximating Rational Numbers by F

• Page 168 and 169:

Approximating Rational Numbers by F

• Page 170 and 171:

Approximating Rational Numbers by F

• Page 172 and 173:

Approximating Rational Numbers by F

• Page 174 and 175:

Approximating Rational Numbers by F

• Page 176 and 177:

Cryptographic and Physical Zero-Kno

• Page 178 and 179:

Cryptographic and Physical Zero-Kno

• Page 180 and 181:

Cryptographic and Physical Zero-Kno

• Page 182 and 183:

Cryptographic and Physical Zero-Kno

• Page 184 and 185:

Cryptographic and Physical Zero-Kno

• Page 186 and 187:

Cryptographic and Physical Zero-Kno

• Page 188 and 189:

Cryptographic and Physical Zero-Kno

• Page 190 and 191:

Cryptographic and Physical Zero-Kno

• Page 192 and 193:

Sorting the Slow Way: An Analysis o

• Page 194 and 195:

Sorting the Slow Way 185 We come to

• Page 196 and 197:

Sorting the Slow Way 187 whichintur

• Page 198 and 199:

Sorting the Slow Way 189 Unfortunat

• Page 200 and 201:

Sorting the Slow Way 191 We can use

• Page 202 and 203:

Sorting the Slow Way 193 stops does

• Page 204 and 205:

• Page 206 and 207:

5 Conclusions Sorting the Slow Way

• Page 208 and 209:

0 2 1 2 1 4 2 4 3 0 2 The Troubles

• Page 210 and 211:

≥ 1 ≥ 1 The Troubles of Interio

• Page 212 and 213:

5 5 5 3 3 3 3 3 2 2 5 5 5 3 3 3 3 3

• Page 214 and 215:

The Troubles of Interior Design 205

• Page 216 and 217:

≥ 1 ≥ 1 The Troubles of Interio

• Page 218 and 219:

The Troubles of Interior Design 209

• Page 220 and 221:

5 5 3 3 3 2 5 0 3 5 0 The Troubles

• Page 222 and 223:

Drawing Borders Efficiently Kazuo I

• Page 224 and 225:

Drawing Borders Efficiently 215 As

• Page 226 and 227:

Drawing Borders Efficiently 217 (1)

• Page 228 and 229:

Drawing Borders Efficiently 219 Tab

• Page 230 and 231:

Fig. 8. Pattern P Drawing Borders E

• Page 232 and 233:

1 2 3 4 5 6 7 1 2 3 4 5 6 7 8 9 (1)

• Page 234 and 235:

Fig. 11. ProofofProposition1 Drawin

• Page 236 and 237:

The Ferry Cover Problem Michael Lam

• Page 238 and 239:

The Ferry Cover Problem 229 Given a

• Page 240 and 241:

The Ferry Cover Problem 231 For |V

• Page 242 and 243:

The Ferry Cover Problem 233 Trip-Co

• Page 244 and 245:

The Ferry Cover Problem 235 the col

• Page 246 and 247:

The Ferry Cover Problem 237 5 The T

• Page 248 and 249:

The Ferry Cover Problem 239 there e

• Page 250 and 251:

v n-1 v 0 v 1 Web Marshals Fighting

• Page 252 and 253:

Web Marshals Fighting Curly Link Fa

• Page 254 and 255:

n -2 n -1 Web Marshals Fighting Cur

• Page 256 and 257:

v n-1 v 0 C 1 v 1 Web Marshals Figh

• Page 258 and 259:

Intruder Capture in Sierpiński Gra

• Page 260 and 261:

Intruder Capture in Sierpiński Gra

• Page 262 and 263:

Intruder Capture in Sierpiński Gra

• Page 264 and 265:

H 1 a) 2 agents, 2 moves, 2 time st

• Page 266 and 267:

Intruder Capture in Sierpiński Gra

• Page 268 and 269:

Intruder Capture in Sierpiński Gra

• Page 270 and 271:

Intruder Capture in Sierpiński Gra

• Page 272 and 273:

On the Complexity of the Traffic Gr

• Page 274 and 275:

On the Complexity of the Traffic Gr

• Page 276 and 277:

On the Complexity of the Traffic Gr

• Page 278 and 279:

On the Complexity of the Traffic Gr

• Page 280 and 281:

On the Complexity of the Traffic Gr

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