The single-source min-cost multicast problem, which can be framed as a convex optimization problem with the use of network codes and convex increasing edge costs is considered. A decentralized approach to this problem is presented by Lun, Ratnakar et. al. for the case where all users cooperate

paging, a setting in which the access cost is not convex. The paging rule corresponding to move-to-front is the “least recently used” (LRU) replacement rule. We analyze the amortized complexity of LRU, showing that its efficiency differs from that of the offline paging rule (Belady’s MIN algorithm) by a

methods based on the dual extragradient algorithm (Nesterov, 2003). The projection step can be solved using dynamic programming or combinatorial algorithms for min-cost convex flow, depending on the structure of the problem. We show that this approach provides a memory-efficient alternative

algorithms for min-cost convex flow. We provide linear convergence guarantees for our method and present experiments on two very different structured prediction tasks: 3D image segmentation and word alignment, illustrating the favorable scaling properties of our algorithm.

. Thus, we examine how changes in credit spreads respond to proxies for both changes in the probability of future default and for changes in the recovery rate. Separately, recent empirical studies find that the corporate bond market tends to have relatively high transactions costs and low volume. 1

Abstract not found

Abstract—We study multicast in a non-cooperative environment where information flows selfishly route themselves through the cheapest paths available. The main challenge is to enforce such selfish multicast flows to stabilize at a socially optimal operating point incurring minimum total edge cost

this report is restricted to network flow problems. Several classes of nonlinear network optimization problems have benefited from the design and implementation of massively parallel algorithms. For a recent survey see Zenios [1991]. Interestingly, nonlinear problems are much easier to solve

updated as arrivals of wheelchair passengers are announced. We solve this min-cost flow problem using network flow techniques such as price functions and the repeated use of Dijkstra’s algorithm. Our algorithm runs in an efficient polynomial time. We prove a theorem stating that to find a no

Abstract—We study multicast in a non-cooperative environment where information flows selfishly route themselves through the cheapest paths available. The main challenge is to enforce such selfish multicast flows to stabilize at a socially optimal operating point incurring minimum total edge cost