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SPIRE
2005
Springer
14 years 1 months ago
Using the k-Nearest Neighbor Graph for Proximity Searching in Metric Spaces
Proximity searching consists in retrieving from a database, objects that are close to a query. For this type of searching problem, the most general model is the metric space, where...
Rodrigo Paredes, Edgar Chávez
PRL
2011
12 years 10 months ago
Structural matching of 2D electrophoresis gels using deformed graphs
2D electrophoresis is a well known method for protein separation which is extremely useful in the field of proteomics. Each spot in the image represents a protein accumulation an...
Alexandre Noma, Alvaro Pardo, Roberto Marcondes Ce...
JMLR
2010
144views more  JMLR 2010»
13 years 2 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
13 years 8 months ago
An EDA based on local markov property and gibbs sampling
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
Siddhartha Shakya, Roberto Santana
SIGIR
2006
ACM
14 years 1 months ago
Contextual search and name disambiguation in email using graphs
Similarity measures for text have historically been an important tool for solving information retrieval problems. In many interesting settings, however, documents are often closel...
Einat Minkov, William W. Cohen, Andrew Y. Ng