Titlebook: Web and Internet Economics; 13th International C Nikhil R. Devanur,Pinyan Lu Conference proceedings 2017 Springer International Publishing

Fester

真繁榮

The Asymptotic Behavior of the Price of Anarchy, hand, for a large class of cost functions (including all polynomials), the price of anarchy . converge to 1 in both heavy and light traffic conditions, and irrespective of the network topology and the number of O/D pairs in the network.

緊張過(guò)度

殺子女者

Approximate Efficiency in Matching Markets,f the so-called . and the recently-proposed . over the .. Furthermore, we provide the first formal statement and analysis of the ., which is conceptually simpler than the Boston mechanism and has a comparable efficiency guarantee.

果核

A Characterization of Undirected Graphs Admitting Optimal Cost Shares,rk design games: an undirected graph is efficient if and only if it does not contain (at least) one out of .. Our characterization implies that several graph classes are efficient: generalized series-parallel graphs, fan and wheel graphs and graphs with small cycles.

Intervention

A Characterization of Undirected Graphs Admitting Optimal Cost Shares,rk design games: an undirected graph is efficient if and only if it does not contain (at least) one out of .. Our characterization implies that several graph classes are efficient: generalized series-parallel graphs, fan and wheel graphs and graphs with small cycles.

勤勞

昏迷狀態(tài)

神圣不可

,Don’t Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximieverage the relation between the spread of cascades and the community structure of social networks. We present “worst-case” theoretical results proving that in certain settings our algorithm outputs seed sets that are a factor of . more influential than those of the greedy algorithm, where . is the

虛假

,Don’t Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximieverage the relation between the spread of cascades and the community structure of social networks. We present “worst-case” theoretical results proving that in certain settings our algorithm outputs seed sets that are a factor of . more influential than those of the greedy algorithm, where . is the