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KDD
2007
ACM
149views Data Mining» more  KDD 2007»
14 years 8 months ago
Partial example acquisition in cost-sensitive learning
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
Victor S. Sheng, Charles X. Ling
ICDM
2005
IEEE
163views Data Mining» more  ICDM 2005»
14 years 1 months ago
Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...
Thomas Takeo Osugi, Kun Deng, Stephen D. Scott
PDP
2008
IEEE
14 years 2 months ago
Load Balancing Distributed Inverted Files: Query Ranking
Search engines use inverted files as index data structures to speed up the solution of user queries. The index is distributed on a set of processors forming a cluster of computer...
Carlos Gomez-Pantoja, Mauricio Marín
SWAT
2004
Springer
125views Algorithms» more  SWAT 2004»
14 years 29 days ago
The Optimal Online Algorithms for Minimizing Maximum Lateness
It is well known that the Earliest-Deadline-First (EDF) and the Least-Laxity-First (LLF) algorithms are optimal algorithms for the problem of preemptively scheduling jobs that arr...
Patchrawat Uthaisombut
SCHEDULING
2011
13 years 2 months ago
On robust online scheduling algorithms
While standard parallel machine scheduling is concerned with good assignments of jobs to machines, we aim to understand how the quality of an assignment is affected if the jobs...
Michael Gatto, Peter Widmayer