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» Maximal Vector Computation in Large Data Sets
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ACL
2011
14 years 10 months ago
Jointly Learning to Extract and Compress
We learn a joint model of sentence extraction and compression for multi-document summarization. Our model scores candidate summaries according to a combined linear model whose fea...
Taylor Berg-Kirkpatrick, Dan Gillick, Dan Klein
ICDE
2009
IEEE
133views Database» more  ICDE 2009»
16 years 1 months ago
STAR: Steiner-Tree Approximation in Relationship Graphs
— Large graphs and networks are abundant in modern information systems: entity-relationship graphs over relational data or Web-extracted entities, biological networks, social onl...
Gjergji Kasneci, Maya Ramanath, Mauro Sozio, Fabia...
ISPASS
2006
IEEE
16 years 13 days ago
Modeling TCAM power for next generation network devices
Applications in Computer Networks often require high throughput access to large data structures for lookup and classification. Many advanced algorithms exist to speed these searc...
Banit Agrawal, Timothy Sherwood
ICCS
2007
Springer
16 years 17 days ago
Dynamic Tracking of Facial Expressions Using Adaptive, Overlapping Subspaces
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
Dimitris N. Metaxas, Atul Kanaujia, Zhiguo Li
CP
2003
Springer
15 years 11 months ago
A SAT-Based Approach to Multiple Sequence Alignment
Multiple sequence alignment is a central problem in Bioinformatics. A known integer programming approach is to apply branch-and-cut to exponentially large graph-theoretic models. T...
Steven David Prestwich, Desmond G. Higgins, Orla O...