Preface |
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xi | |
Course Outline |
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xv | |
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1 | (54) |
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1 | (1) |
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1.2 Graphs and Their Degree and Connectivity Structure |
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2 | (3) |
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1.3 Complex Networks: the Infamous Internet Example |
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5 | (6) |
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1.4 Scale-Free, Highly Connected and Small-World Graph Sequences |
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11 | (5) |
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1.5 Further Network Statistics |
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16 | (4) |
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1.6 Other Real-World Network Examples |
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20 | (20) |
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40 | (5) |
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1.8 Random Graph Models for Complex Networks |
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45 | (4) |
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49 | (1) |
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1.10 Notes and Discussion |
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50 | (2) |
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1.11 Exercises for Chapter 1 |
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52 | (3) |
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55 | (60) |
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57 | (30) |
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2.1 Convergence of Random Variables |
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57 | (5) |
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62 | (3) |
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65 | (4) |
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69 | (4) |
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73 | (5) |
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2.6 Order Statistics and Extreme Value Theory |
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78 | (4) |
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82 | (1) |
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2.8 Exercises for Chapter 2 |
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83 | (4) |
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87 | (28) |
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3.1 Survival versus Extinction |
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87 | (4) |
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91 | (1) |
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3.3 Random-Walk Perspective to Branching Processes |
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92 | (4) |
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3.4 Supercritical Branching Processes |
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96 | (4) |
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3.5 Hitting-Time Theorem and the Total Progeny |
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100 | (2) |
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3.6 Properties of Poisson Branching Processes |
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102 | (5) |
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3.7 Binomial and Poisson Branching Processes |
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107 | (2) |
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109 | (2) |
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3.9 Exercises for Chapter 3 |
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111 | (4) |
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115 | (62) |
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4 Phase Transition for the Erdos--Renyi Random Graph |
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117 | (33) |
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117 | (5) |
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4.2 Comparisons to Branching Processes |
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122 | (2) |
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4.3 The Subcritical Regime |
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124 | (6) |
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4.4 The Supercritical Regime |
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130 | (9) |
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4.5 CLT for the Giant Component |
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139 | (6) |
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145 | (1) |
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4.7 Exercises for Chapter 4 |
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146 | (4) |
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5 Erdos--Renyi Random Graph Revisited |
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150 | (27) |
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5.1 The Critical Behavior |
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150 | (6) |
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5.2 Critical Erdos--Renyi Random Graphs with Martingales |
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156 | (8) |
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5.3 Connectivity Threshold |
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164 | (4) |
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5.4 Degree Sequence of the Erdos--Renyi Random Graph |
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168 | (4) |
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172 | (2) |
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5.6 Exercises for Chapter 5 |
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174 | (3) |
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Part III Models for Complex Networks |
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177 | (124) |
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Intermezzo: Back to Real-World Networks... |
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179 | (4) |
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6 Generalized Random Graphs |
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183 | (33) |
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6.1 Motivation of the Model |
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183 | (1) |
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6.2 Introduction of the Model |
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184 | (6) |
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6.3 Degrees in the Generalized Random Graph |
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190 | (4) |
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6.4 Degree Sequence of Generalized Random Graph |
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194 | (3) |
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6.5 Generalized Random Graph with I.I.D. Weights |
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197 | (2) |
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6.6 Generalized Random Graph Conditioned on Its Degrees |
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199 | (4) |
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6.7 Asymptotic Equivalence of Inhomogeneous Random Graphs |
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203 | (4) |
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6.8 Related Inhomogeneous Random Graph Models |
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207 | (2) |
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209 | (1) |
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6.10 Exercises for Chapter 6 |
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210 | (6) |
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216 | (40) |
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7.1 Motivation for the Configuration Model |
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216 | (2) |
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7.2 Introduction to the Model |
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218 | (9) |
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7.3 Erased Configuration Model |
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227 | (5) |
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7.4 Repeated Configuration Model: Simplicity Probability |
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232 | (4) |
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7.5 Uniform Simple Graphs and Generalized Random Graphs |
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236 | (5) |
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7.6 Configuration Model with I.I.D. Degrees |
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241 | (4) |
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7.7 Related Results on the Configuration Model |
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245 | (3) |
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7.8 Related Random Graph Models |
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248 | (2) |
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250 | (2) |
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7.10 Exercises for Chapter 7 |
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252 | (4) |
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8 Preferential Attachment Models |
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256 | (45) |
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8.1 Motivation for the Preferential Attachment Model |
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256 | (3) |
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8.2 Introduction of the Model |
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259 | (3) |
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8.3 Degrees of Fixed Vertices |
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262 | (2) |
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8.4 Degree Sequences of Preferential Attachment Models |
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264 | (3) |
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8.5 Concentration of the Degree Sequence |
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267 | (3) |
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8.6 Expected Degree Sequence |
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270 | (13) |
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8.7 Maximal Degree in Preferential Attachment Models |
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283 | (5) |
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8.8 Related Results for Preferential Attachment Models |
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288 | (2) |
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8.9 Related Preferential Attachment Models |
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290 | (4) |
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8.10 Notes and Discussion |
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294 | (3) |
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8.11 Exercises for Chapter 8 |
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297 | (4) |
Appendix |
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301 | (3) |
Glossary |
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304 | (2) |
References |
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306 | (11) |
Index |
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317 | |