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AUTOMATICA
2008
139views more  AUTOMATICA 2008»
15 years 2 months ago
Structured low-rank approximation and its applications
Fitting data by a bounded complexity linear model is equivalent to low-rank approximation of a matrix constructed from the data. The data matrix being Hankel structured is equival...
Ivan Markovsky
ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
15 years 8 months ago
gApprox: Mining Frequent Approximate Patterns from a Massive Network
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
130
Voted
VLDB
2005
ACM
129views Database» more  VLDB 2005»
15 years 8 months ago
Sketching Streams Through the Net: Distributed Approximate Query Tracking
Emerging large-scale monitoring applications require continuous tracking of complex dataanalysis queries over collections of physicallydistributed streams. Effective solutions hav...
Graham Cormode, Minos N. Garofalakis
VLDB
1998
ACM
111views Database» more  VLDB 1998»
15 years 6 months ago
Filtering with Approximate Predicates
Approximate predicates can be used to reduce the number of comparisons made by expensive, complex predicates. For example, to check if a point is within a region (expensive predic...
Narayanan Shivakumar, Hector Garcia-Molina, Chandr...
139
Voted
AAAI
2006
15 years 3 months ago
Compact, Convex Upper Bound Iteration for Approximate POMDP Planning
Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...