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» Improving Random Projections Using Marginal Information
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KAIS
2011
129views more  KAIS 2011»
14 years 6 months ago
Counting triangles in real-world networks using projections
Triangle counting is an important problem in graph mining. Two frequently used metrics in complex network analysis which require the count of triangles are the clustering coefficie...
Charalampos E. Tsourakakis
SIGIR
2009
ACM
15 years 6 months ago
Extracting structured information from user queries with semi-supervised conditional random fields
When search is against structured documents, it is beneficial to extract information from user queries in a format that is consistent with the backend data structure. As one step...
Xiao Li, Ye-Yi Wang, Alex Acero
COMSWARE
2007
IEEE
15 years 6 months ago
Sensor Network Deployment For Agronomical Data Gathering in Semi-Arid Regions
— We share our experience in planning, designing and deploying a wireless sensor network of one square kilometre area. Environmental data such as soil moisture, temperature, baro...
Tamma V. Prabhakar, N. V. Chalapathi Rao, M. S. Su...
TSD
2009
Springer
15 years 4 months ago
Combining Text Vector Representations for Information Retrieval
Abstract. This paper suggests a novel representation for documents that is intended to improve precision. This representation is generated by combining two central techniques: Rand...
Maya Carrillo, Chris Eliasmith, Aurelio Lóp...
NIPS
2004
15 years 1 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...