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» Approximation Algorithms for Requirement Cut on Graphs
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SIAMJO
2010
136views more  SIAMJO 2010»
14 years 4 months ago
A New Exchange Method for Convex Semi-Infinite Programming
In this paper we propose a new exchange method for solving convex semi-infinite programming (CSIP) problems. We introduce a new dropping-rule in the proposed exchange algorithm, wh...
Liping Zhang, Soon-Yi Wu, Marco A. López
IJCNN
2000
IEEE
15 years 2 months ago
Piecewise Linear Homeomorphisms: The Scalar Case
The class of piecewise linear homeomorphisms (PLH) provides a convenient functional representation for many applications wherein an approximation to data is required that is inver...
Richard E. Groff, Daniel E. Koditschek, Pramod P. ...
IJCNN
2006
IEEE
15 years 3 months ago
A Comparison between Recursive Neural Networks and Graph Neural Networks
— Recursive Neural Networks (RNNs) and Graph Neural Networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing fram...
Vincenzo Di Massa, Gabriele Monfardini, Lorenzo Sa...
JCO
2006
126views more  JCO 2006»
14 years 9 months ago
Minimum power assignment in wireless ad hoc networks with spanner property
Power assignment for wireless ad hoc networks is to assign a power for each wireless node such that the induced communication graph has some required properties. Recently research ...
Yu Wang 0003, Xiang-Yang Li
FOCS
2008
IEEE
15 years 4 months ago
Beating the Random Ordering is Hard: Inapproximability of Maximum Acyclic Subgraph
We prove that approximating the Max Acyclic Subgraph problem within a factor better than 1/2 is Unique-Games hard. Specifically, for every constant ε > 0 the following holds:...
Venkatesan Guruswami, Rajsekar Manokaran, Prasad R...