Titlebook: Algorithm Theory – SWAT 2008; 11th Scandinavian Wo Joachim Gudmundsson Conference proceedings 2008 The Editor(s) (if applicable) and The Au

Abominate

Batch Coloring Flat Graphs and Thinmes. This gives rise to two types of .: . and ., respectively..We give the first . for batch sum coloring on several classes of ”non-thick” graphs that arise in applications. This includes paths, trees, partial .-trees, and planar graphs. Also, we give an improved .(...) exact algorithm for the max-coloring problem on paths.

字的误用

https://doi.org/10.1007/978-3-531-19833-0 the years, a fascinating theory has started forming around a convex program given by Eisenberg and Gale in 1959. Besides market equilibria, this theory touches on such disparate topics as TCP congestion control and efficient solvability of nonlinear programs by combinatorial means. Our work shows t

永久

Die Herausforderungen der Demokratie,In particular, we show that the problem of deciding whether each of . given targets can be tracked with 90° is NP-complete. For the special case where the cameras are placed along a single line while the targets are located anywhere in the plane, we show a 2-approximation both for the sum of trackin

新鲜

甜食

affluent

https://doi.org/10.1007/978-3-663-09580-4ality-sensitive version of the standard practice—path copying—costing . time and space for modification of a node at depth ., which is expensive when performing many deep but nearby updates. Our second data structure supporting finger movement in . time and no space, while modifications take . time

柔软

补角

Nash Bargaining Via Flexible Budget Markets the years, a fascinating theory has started forming around a convex program given by Eisenberg and Gale in 1959. Besides market equilibria, this theory touches on such disparate topics as TCP congestion control and efficient solvability of nonlinear programs by combinatorial means. Our work shows t

强制性

cruise

Bounded Unpopularity Matchingsf edges in . and . is the number of nodes) provided a certain graph . admits a matching that matches all people. We also describe a sequence of graphs: . = .., ..,...,.. such that if .. admits a matching that matches all people, then we can compute in . time a matching . such that .(.) ≤ . − 1 and .