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NIPS
1998
13 years 11 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
IMC
2007
ACM
13 years 11 months ago
Quality-of-service class specific traffic matrices in ip/mpls networks
In this paper we consider the problem of determining traffic matrices for end-to-end demands in an IP/MPLS network that supports multiple quality of service (QoS) classes. More pr...
Stefan Schnitter, Franz Hartleb, Martin Horneffer
SIGCOMM
2006
ACM
14 years 4 months ago
Beyond bloom filters: from approximate membership checks to approximate state machines
Many networking applications require fast state lookups in a concurrent state machine, which tracks the state of a large number of flows simultaneously. We consider the question ...
Flavio Bonomi, Michael Mitzenmacher, Rina Panigrah...
JAIR
2008
157views more  JAIR 2008»
13 years 10 months ago
Learning to Reach Agreement in a Continuous Ultimatum Game
It is well-known that acting in an individually rational manner, according to the principles of classical game theory, may lead to sub-optimal solutions in a class of problems nam...
Steven de Jong, Simon Uyttendaele, Karl Tuyls
CORR
2010
Springer
114views Education» more  CORR 2010»
13 years 8 months ago
On weakly optimal partitions in modular networks
Abstract. Modularity was introduced as a measure of goodness for the community structure induced by a partition of the set of vertices in a graph. Then, it also became an objective...
José Ignacio Alvarez-Hamelin, Beiró ...