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JACM
2006
99views more  JACM 2006»
15 years 4 months ago
Finding a maximum likelihood tree is hard
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
Benny Chor, Tamir Tuller
GLOBECOM
2010
IEEE
15 years 2 months ago
SplitAP: Leveraging Wireless Network Virtualization for Flexible Sharing of WLANs
Providing air-time guarantees across a group of clients forms a fundamental building block in sharing an access point (AP) across different virtual network providers. Though this p...
Gautam D. Bhanage, Dipti Vete, Ivan Seskar, Dipank...
SIGMOD
2010
ACM
191views Database» more  SIGMOD 2010»
15 years 4 months ago
Data conflict resolution using trust mappings
In massively collaborative projects such as scientific or community databases, users often need to agree or disagree on the content of individual data items. On the other hand, tr...
Wolfgang Gatterbauer, Dan Suciu
TSMC
2008
100views more  TSMC 2008»
15 years 4 months ago
Instruction-Matrix-Based Genetic Programming
In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In th...
Gang Li, Jin Feng Wang, Kin-Hong Lee, Kwong-Sak Le...
CORR
2011
Springer
139views Education» more  CORR 2011»
14 years 8 months ago
Clustering Partially Observed Graphs via Convex Optimization
This paper considers the problem of clustering a partially observed unweighted graph – i.e. one where for some node pairs we know there is an edge between them, for some others ...
Ali Jalali, Yudong Chen, Sujay Sanghavi, Huan Xu