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KDD
2009
ACM
227views Data Mining» more  KDD 2009»
14 years 8 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
SIGMOD
2009
ACM
171views Database» more  SIGMOD 2009»
14 years 7 months ago
GAMPS: compressing multi sensor data by grouping and amplitude scaling
We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within...
Sorabh Gandhi, Suman Nath, Subhash Suri, Jie Liu
STOC
2004
ACM
121views Algorithms» more  STOC 2004»
14 years 7 months ago
Lower bounds for dynamic connectivity
We prove an (lg n) cell-probe lower bound on maintaining connectivity in dynamic graphs, as well as a more general trade-off between updates and queries. Our bound holds even if t...
Mihai Patrascu, Erik D. Demaine
SIGMOD
2008
ACM
101views Database» more  SIGMOD 2008»
14 years 7 months ago
Pay-as-you-go user feedback for dataspace systems
A primary challenge to large-scale data integration is creating semantic equivalences between elements from different data sources that correspond to the same real-world entity or...
Shawn R. Jeffery, Michael J. Franklin, Alon Y. Hal...
SIGMOD
2010
ACM
207views Database» more  SIGMOD 2010»
14 years 6 days ago
Automatic contention detection and amelioration for data-intensive operations
To take full advantage of the parallelism offered by a multicore machine, one must write parallel code. Writing parallel code is difficult. Even when one writes correct code, the...
John Cieslewicz, Kenneth A. Ross, Kyoho Satsumi, Y...