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GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
15 years 2 months ago
Studying the Advantages of a Messy Evolutionary Algorithm for Natural Language Tagging
The process of labeling each word in a sentence with one of its lexical categories (noun, verb, etc) is called tagging and is a key step in parsing and many other language processi...
Lourdes Araujo
3DOR
2008
15 years 2 days ago
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
Guillaume Lavoué, Christian Wolf
71
Voted
BMCBI
2008
132views more  BMCBI 2008»
14 years 9 months ago
Mixture models for analysis of melting temperature data
Background: In addition to their use in detecting undesired real-time PCR products, melting temperatures are useful for detecting variations in the desired target sequences. Metho...
Christoffer Nellåker, Fredrik Uhrzander, Joa...
ICML
2005
IEEE
15 years 10 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
INFOCOM
2010
IEEE
14 years 8 months ago
A Frequency Domain Model to Predict the Estimation Accuracy of Packet Sampling
—In network measurement systems, packet sampling techniques are usually adopted to reduce the overall amount of data to collect and process. Being based on a subset of packets, t...
Luigi Alfredo Grieco, Chadi Barakat