Learning-aided stochastic network optimization with state prediction

L Huang, M Chen, Y Liu - IEEE/ACM Transactions on …, 2018 - ieeexplore.ieee.org
We investigate the problem of stochastic network optimization in the presence of state
prediction and nonstationarity. Based on a novel state prediction model featured with a …

Non-stationary stochastic network optimization with imperfect estimations

Y Liu, Z Liu, Y Yang - 2019 IEEE 39th International Conference …, 2019 - ieeexplore.ieee.org
We investigate the problem of stochastic network optimization in presence of non-stationarity
and estimations of average states in the future. Specifically, we first prove that the widely …

Learning-aided stochastic network optimization with imperfect state prediction

L Huang, M Chen, Y Liu - Proceedings of the 18th ACM International …, 2017 - dl.acm.org
We investigate the problem of stochastic network optimization in the presence of imperfect
state prediction and non-stationarity. Based on a novel distribution-accuracy curve …

New algorithms for edge induced könig-egerváry subgraph based on gallai-edmonds decomposition

Q Feng, G Tan, S Zhu, B Fu… - … Symposium on Algorithms …, 2018 - drops.dagstuhl.de
König-Egerváry graphs form an important graph class which has been studied extensively in
graph theory. Much attention has also been paid on König-Egerváry subgraphs and König …

Gallai-Edmonds decomposition of unicyclic graphs from null space

LE Allem, DA Jaume, G Molina… - … . Vol. 1 (2022), p. 47–64, 2022 - lume.ufrgs.br
Gallai-Edmonds decomposition of unicyclic graphs from null space Page 1 American Journal
of Combinatorics Research Article Volume 1 (2022), Pages 47–64 Gallai-Edmonds …

Approximation Algorithms for Maximum Vertex-Weighted Matching

A Al-Herz - 2019 - search.proquest.com
We consider the maximum vertex-weighted matching problem (MVM), in which non-negative
weights are assigned to the vertices of a graph, and the weight of a matching is the sum of …