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VLDB
2005
ACM
196views Database» more  VLDB 2005»
15 years 7 months ago
Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling
Emerging data stream management systems approach the challenge of massive data distributions which arrive at high speeds while there is only small storage by summarizing and minin...
Graham Cormode, S. Muthukrishnan, Irina Rozenbaum
LCPC
2009
Springer
15 years 6 months ago
Using the Meeting Graph Framework to Minimise Kernel Loop Unrolling for Scheduled Loops
This paper improves our previous research effort [1] by providing an efficient method for kernel loop unrolling minimisation in the case of already scheduled loops, where circular...
Mounira Bachir, David Gregg, Sid Ahmed Ali Touati
114
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AIPS
2000
15 years 3 months ago
On-line Scheduling via Sampling
1 We consider the problem of scheduling an unknown sequence of tasks for a single server as the tasks arrive with the goal off maximizing the total weighted value of the tasks serv...
Hyeong Soo Chang, Robert Givan, Edwin K. P. Chong
131
Voted
JMLR
2006
169views more  JMLR 2006»
15 years 1 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
215
Voted
POPL
2006
ACM
16 years 2 months ago
A hierarchical model of data locality
In POPL 2002, Petrank and Rawitz showed a universal result-finding optimal data placement is not only NP-hard but also impossible to approximate within a constant factor if P = NP...
Chengliang Zhang, Chen Ding, Mitsunori Ogihara, Yu...