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113
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KDD
1998
ACM
123views Data Mining» more  KDD 1998»
15 years 6 months ago
Scaling Clustering Algorithms to Large Databases
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Paul S. Bradley, Usama M. Fayyad, Cory Reina
RECSYS
2010
ACM
15 years 2 months ago
Incremental collaborative filtering via evolutionary co-clustering
Collaborative filtering is a popular approach for building recommender systems. Current collaborative filtering algorithms are accurate but also computationally expensive, and so ...
Mohammad Khoshneshin, W. Nick Street
98
Voted
AUTOMATICA
2008
85views more  AUTOMATICA 2008»
15 years 1 months ago
Nonlinear vehicle side-slip estimation with friction adaptation
A nonlinear observer for estimation of the longitudinal velocity, lateral velocity, and yaw rate of a vehicle, designed for the purpose of vehicle side-slip estimation, is modifie...
Håvard Fjær Grip, Lars Imsland, Tor Ar...
JUCS
2010
135views more  JUCS 2010»
14 years 8 months ago
Internal Representation of Database Views
: Although a database view embodies partial information about the state of the main schema, the state of the view schema is a quotient (and not a subset) of the state of the main s...
Stephen J. Hegner
SDM
2003
SIAM
123views Data Mining» more  SDM 2003»
15 years 3 months ago
Fast Online SVD Revisions for Lightweight Recommender Systems
The singular value decomposition (SVD) is fundamental to many data modeling/mining algorithms, but SVD algorithms typically have quadratic complexity and require random access to ...
Matthew Brand