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TEC
2008
115views more  TEC 2008»
13 years 7 months ago
Function Approximation With XCS: Hyperellipsoidal Conditions, Recursive Least Squares, and Compaction
An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
HYBRID
2007
Springer
14 years 1 months ago
Approximation of the Joint Spectral Radius of a Set of Matrices Using Sum of Squares
We provide an asymptotically tight, computationally efficient approximation of the joint spectral radius of a set of matrices using sum of squares (SOS) programming. The approach i...
Pablo A. Parrilo, Ali Jadbabaie
STACS
2010
Springer
14 years 17 days ago
Approximate Shortest Paths Avoiding a Failed Vertex: Optimal Size Data Structures for Unweighted Graphs
Let G = (V, E) be any undirected graph on V vertices and E edges. A path P between any two vertices u, v ∈ V is said to be t-approximate shortest path if its length is at most t ...
Neelesh Khanna, Surender Baswana
CORR
2010
Springer
135views Education» more  CORR 2010»
13 years 7 months ago
Approximate Shortest Paths Avoiding a Failed Vertex: Optimal Size Data Structures for Unweighted Graph
Let G = (V, E) be any undirected graph on V vertices and E edges. A path P between any two vertices u, v V is said to be t-approximate shortest path if its length is at most t tim...
Neelesh Khanna Surender Baswana
ALGORITHMICA
1999
102views more  ALGORITHMICA 1999»
13 years 7 months ago
Approximating Latin Square Extensions
In this paper, we consider the following question: what is the maximum number of entries that can be added to a partially lled latin square? The decision version of this question ...
Ravi Kumar, Alexander Russell, Ravi Sundaram