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1 | (14) |
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2 | (3) |
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An approximation algorithm for cardinality vertex cover |
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3 | (1) |
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Can the approximation guarantee the improved? |
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3 | (2) |
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Well-characterized problems and min-max relations |
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5 | (2) |
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7 | (3) |
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10 | (5) |
Part I. Combinatorial Algorithms |
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15 | (12) |
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16 | (1) |
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17 | (2) |
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Application to shortest superstring |
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19 | (3) |
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22 | (4) |
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26 | (1) |
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27 | (11) |
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27 | (3) |
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28 | (2) |
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30 | (3) |
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A simple factor 2 algorithm |
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31 | (1) |
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Improving the factor to 3/2 |
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32 | (1) |
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33 | (4) |
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37 | (1) |
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38 | (9) |
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38 | (2) |
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The minimum k-cut problem |
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40 | (4) |
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44 | (2) |
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46 | (1) |
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47 | (7) |
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Parametric pruning applied to metric k-center |
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47 | (3) |
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50 | (2) |
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52 | (1) |
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53 | (1) |
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54 | (7) |
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Cyclomatic weighted graphs |
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54 | (3) |
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Layering applied to feedback vertex set |
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57 | (3) |
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60 | (1) |
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60 | (1) |
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61 | (7) |
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61 | (3) |
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64 | (2) |
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Achieving half the optimal compression |
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66 | (1) |
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66 | (1) |
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67 | (1) |
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68 | (6) |
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A pseudo-polynomial time algorithm for knapsack |
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69 | (1) |
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69 | (2) |
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Strong NP-hardness and the existence of FPTAS's |
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71 | (1) |
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Is an FPTAS the most desirable approximation algorithm? |
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72 | (1) |
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72 | (1) |
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73 | (1) |
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74 | (5) |
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74 | (3) |
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77 | (1) |
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78 | (1) |
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Minimum Makespan Scheduling |
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79 | (5) |
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79 | (1) |
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A PTAS for minimum makespan |
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80 | (3) |
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Bin packing with fixed number of object sizes |
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81 | (1) |
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Reducing makespan to restricted bin packing |
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81 | (2) |
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83 | (1) |
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83 | (1) |
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84 | (9) |
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84 | (3) |
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87 | (2) |
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89 | (1) |
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89 | (4) |
Part II. LP-Based Algorithms |
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Introduction to LP-Duality |
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93 | (15) |
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93 | (4) |
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Min-max relations and LP-duality |
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97 | (3) |
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Two fundamental algorithm design techniques |
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100 | (3) |
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A comparison of the techniques and the notion of integrality gap |
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101 | (2) |
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103 | (4) |
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107 | (1) |
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Set Cover via Dual Fitting |
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108 | (11) |
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Dual-fitting-based analysis for the greedy set cover algorithm |
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108 | (4) |
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Can the approximation guarantee be improved? |
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111 | (1) |
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Generalizations of set cover |
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112 | (4) |
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Dual fitting applied to constrained set multicover |
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112 | (4) |
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116 | (2) |
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118 | (1) |
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Rounding Applied to Set Cover |
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119 | (6) |
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A simple rounding algorithm |
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119 | (1) |
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120 | (2) |
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Half-integrality of vertex cover |
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122 | (1) |
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123 | (1) |
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124 | (1) |
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Set Cover via the Primal-Dual Schema |
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125 | (6) |
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125 | (2) |
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Primal-dual schema applied to set cover |
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127 | (2) |
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129 | (1) |
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129 | (2) |
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131 | (9) |
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Dealing with large clauses |
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132 | (1) |
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Derandomizing via the method of conditional expectation |
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132 | (2) |
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Dealing with small clauses via LP-rounding |
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134 | (2) |
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136 | (1) |
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137 | (2) |
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139 | (1) |
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Scheduling on Unrelated Parallel Machines |
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140 | (6) |
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Parametric pruning in an LP setting |
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140 | (1) |
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Properties of extreme point solutions |
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141 | (1) |
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142 | (1) |
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Additional properties of extreme point solutions |
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143 | (1) |
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144 | (1) |
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145 | (1) |
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Multicut and Integer Multicommodity Flow in Trees |
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146 | (9) |
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The problmes and their LP-relaxations |
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146 | (3) |
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Primal-dual schema based algorithm |
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149 | (3) |
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152 | (2) |
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154 | (1) |
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155 | (13) |
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An interesting LP-relaxation |
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155 | (2) |
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Randomized rounding algorithm |
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157 | (3) |
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Half-integrality of node multiway cut |
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160 | (3) |
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163 | (4) |
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167 | (1) |
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Multicut in General Graphs |
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168 | (12) |
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168 | (2) |
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LP-rounding-based algorithm |
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170 | (5) |
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Growing a region: the continous process |
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171 | (1) |
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172 | (1) |
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Finding successive regions |
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173 | (2) |
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175 | (1) |
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Some applications of multicut |
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176 | (1) |
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177 | (2) |
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179 | (1) |
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180 | (18) |
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Demands multicommodity flow |
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180 | (1) |
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Linear programming formulation |
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181 | (2) |
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Metrics, cut packings, and l1-embeddability |
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183 | (3) |
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183 | (2) |
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l1-embeddability of metrics |
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185 | (1) |
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Low distortion l1-embeddings for metrics |
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186 | (5) |
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Ensuring that a single edge is not overshrunk |
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187 | (3) |
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Ensuring that no edge is overshrunk |
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190 | (1) |
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LP-rounding-based algorithm |
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191 | (1) |
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192 | (3) |
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192 | (1) |
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192 | (1) |
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193 | (1) |
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Minimum cut linear arrangement |
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194 | (1) |
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195 | (2) |
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197 | (1) |
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198 | (15) |
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198 | (1) |
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Primal-dual schema with synchronization |
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199 | (5) |
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204 | (3) |
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207 | (5) |
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212 | (1) |
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213 | (19) |
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The LP-relaxation and half-integrality |
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213 | (4) |
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The technique of iterated rounding |
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217 | (2) |
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Characterizing extreme point solutions |
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219 | (2) |
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221 | (3) |
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224 | (7) |
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231 | (1) |
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232 | (11) |
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An intuitive understanding of the dual |
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233 | (1) |
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Relaxing primal complementary slackness conditions |
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234 | (1) |
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Primal-dual schema based algorithm |
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235 | (1) |
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236 | (3) |
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238 | (1) |
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238 | (1) |
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239 | (3) |
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242 | (1) |
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243 | (13) |
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243 | (1) |
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244 | (3) |
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247 | (3) |
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248 | (1) |
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249 | (1) |
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249 | (1) |
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250 | (1) |
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A Lagrangian relaxation technique for approximation algorithms |
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250 | (1) |
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251 | (3) |
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254 | (2) |
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256 | (17) |
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Strict quadratic programs and vector programs |
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256 | (2) |
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Properties of positive semidefinite matrices |
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258 | (1) |
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The semidefinite programming problem |
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259 | (2) |
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Randomized rounding algorithm |
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261 | (3) |
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Improving the guarantee for MAX-2SAT |
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264 | (2) |
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266 | (3) |
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269 | (4) |
Part III. Other Topics |
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273 | (21) |
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Bases, determinants, and orthogonality defect |
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274 | (2) |
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The algorithms of Euclid and Gauss |
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276 | (2) |
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Lower bounding OPT using Gram-Schmidt orthogonalization |
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278 | (2) |
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Extension to n dimensions |
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280 | (4) |
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The dual lattice and its algorithmic use |
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284 | (4) |
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288 | (4) |
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292 | (2) |
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294 | (12) |
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295 | (2) |
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297 | (5) |
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Upperbounding the number of near-minimum cuts |
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298 | (2) |
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300 | (2) |
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302 | (3) |
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305 | (1) |
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Hardness of Approximation |
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306 | (28) |
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Reductions, gaps, and hardness factors |
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306 | (3) |
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309 | (2) |
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311 | (2) |
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Hardness of MAX-3SAT with bounded occurence of variables |
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313 | (3) |
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Hardness of vertex cover and Steiner tree |
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316 | (2) |
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318 | (4) |
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322 | (7) |
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The two-prover one-round characterization of NP |
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322 | (2) |
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324 | (1) |
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Reducing error probability by parallel repetition |
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325 | (1) |
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326 | (3) |
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329 | (3) |
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332 | (2) |
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334 | (21) |
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Problems having constant factor algorithms |
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334 | (2) |
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Other optimization problems |
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336 | (2) |
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338 | (5) |
Appendix |
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A An Overview of Complexity Theory for the Algorithm Designer |
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343 | (9) |
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A.1 Certificates and the class NP |
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343 | (1) |
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A.2 Reductions and NP-completeness |
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344 | (1) |
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A.3 NP-optimization problems and approximation algorithms |
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345 | (2) |
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A.3.1 Approximation factor preserving reductions |
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347 | (1) |
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A.4 Randomized complexity classes |
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347 | (1) |
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348 | (3) |
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351 | (1) |
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B Basic Facts from Probability Theory |
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352 | (3) |
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B.1 Expectation and moments |
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352 | (1) |
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B.2 Deviations from the mean |
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353 | (1) |
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354 | (1) |
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354 | (1) |
References |
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355 | (16) |
Problem Index |
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371 | (4) |
Subject Index |
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375 | |