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VLDB
2007
ACM
181views Database» more  VLDB 2007»
14 years 10 months ago
STAR: Self-Tuning Aggregation for Scalable Monitoring
We present STAR, a self-tuning algorithm that adaptively sets numeric precision constraints to accurately and efficiently answer continuous aggregate queries over distributed data...
Navendu Jain, Michael Dahlin, Yin Zhang, Dmitry Ki...
EPIA
2003
Springer
14 years 3 months ago
Mining Low Dimensionality Data Streams of Continuous Attributes
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
Francisco J. Ferrer-Troyano, Jesús S. Aguil...
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
13 years 7 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava
IPPS
2010
IEEE
13 years 7 months ago
A scalable algorithm for maintaining perpetual system connectivity in dynamic distributed systems
We investigate the problem of maintaining a topology with small degree as well as small diameter in a dynamic distributed system such that the system always stays connected and pr...
Tarun Bansal, Neeraj Mittal
FMCAD
2000
Springer
14 years 1 months ago
Scalable Distributed On-the-Fly Symbolic Model Checking
Abstract. This paper presents a scalable method for parallel symbolic on-the-fly model checking in a distributed memory environment. Our method combines a scheme for on-the-fly mod...
Shoham Ben-David, Tamir Heyman, Orna Grumberg, Ass...