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APPROX
2008
Springer
127views Algorithms» more  APPROX 2008»
14 years 12 months ago
Approximating Single Machine Scheduling with Scenarios
In the field of robust optimization, the goal is to provide solutions to combinatorial problems that hedge against variations of the numerical parameters. This constitutes an effor...
Monaldo Mastrolilli, Nikolaus Mutsanas, Ola Svenss...
CORR
2010
Springer
138views Education» more  CORR 2010»
14 years 10 months ago
Data Stream Clustering: Challenges and Issues
Very large databases are required to store massive amounts of data that are continuously inserted and queried. Analyzing huge data sets and extracting valuable pattern in many appl...
Madjid Khalilian, Norwati Mustapha
ACML
2009
Springer
15 years 4 months ago
Coupled Metric Learning for Face Recognition with Degraded Images
Real-world face recognition systems are sometimes confronted with degraded face images, e.g., low-resolution, blurred, and noisy ones. Traditional two-step methods have limited per...
Bo Li, Hong Chang, Shiguang Shan, Xilin Chen
DOCENG
2009
ACM
15 years 4 months ago
Test collection management and labeling system
In order to evaluate the performance of information retrieval and extraction algorithms, we need test collections. A test collection consists of a set of documents, a clearly form...
Eunyee Koh, Andruid Kerne, Sarah Berry
ICDE
2006
IEEE
201views Database» more  ICDE 2006»
15 years 11 months ago
Counting at Large: Efficient Cardinality Estimation in Internet-Scale Data Networks
Counting in general, and estimating the cardinality of (multi-) sets in particular, is highly desirable for a large variety of applications, representing a foundational block for ...
Nikos Ntarmos, Peter Triantafillou, Gerhard Weikum