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» Algorithms for the Sample Mean of Graphs
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APPROX
2008
Springer
119views Algorithms» more  APPROX 2008»
15 years 1 months ago
The Complexity of Distinguishing Markov Random Fields
Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...
Andrej Bogdanov, Elchanan Mossel, Salil P. Vadhan
ISCI
2007
170views more  ISCI 2007»
14 years 11 months ago
Automatic learning of cost functions for graph edit distance
Graph matching and graph edit distance have become important tools in structural pattern recognition. The graph edit distance concept allows us to measure the structural similarit...
Michel Neuhaus, Horst Bunke
JCM
2008
81views more  JCM 2008»
14 years 12 months ago
An Iterative Algorithm for Joint Symbol Timing Recovery and Equalization of Short Bursts
In this work a joint clock recovery (CR) and equalization scheme for short burst transmissions is presented. The joint optimization performance may be pursued by means of both data...
Pietro Savazzi, Paolo Gamba, Lorenzo Favalli
IJON
2010
121views more  IJON 2010»
14 years 9 months ago
Sample-dependent graph construction with application to dimensionality reduction
Graph construction plays a key role on learning algorithms based on graph Laplacian. However, the traditional graph construction approaches of -neighborhood and k-nearest-neighbor...
Bo Yang, Songcan Chen
FOCS
2005
IEEE
15 years 5 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys