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SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 2 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
104
Voted
CVPR
2010
IEEE
15 years 1 months ago
High performance object detection by collaborative learning of Joint Ranking of Granules features
Object detection remains an important but challenging task in computer vision. We present a method that combines high accuracy with high efficiency. We adopt simplified forms of...
Chang Huang, Ramakant Nevatia
139
Voted
BMCBI
2008
149views more  BMCBI 2008»
15 years 28 days ago
All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
Background: Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach ...
Antti Airola, Sampo Pyysalo, Jari Björne, Tap...
CN
2006
163views more  CN 2006»
15 years 26 days ago
A framework for mining evolving trends in Web data streams using dynamic learning and retrospective validation
The expanding and dynamic nature of the Web poses enormous challenges to most data mining techniques that try to extract patterns from Web data, such as Web usage and Web content....
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
106
Voted
NN
2008
Springer
152views Neural Networks» more  NN 2008»
15 years 24 days ago
Analysis of the IJCNN 2007 agnostic learning vs. prior knowledge challenge
We organized a challenge for IJCNN 2007 to assess the added value of prior domain knowledge in machine learning. Most commercial data mining programs accept data pre-formatted in ...
Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C...