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STOC
2004
ACM
118views Algorithms» more  STOC 2004»
16 years 3 days ago
Boosted sampling: approximation algorithms for stochastic optimization
Several combinatorial optimization problems choose elements to minimize the total cost of constructing a feasible solution that satisfies requirements of clients. In the STEINER T...
Anupam Gupta, Martin Pál, R. Ravi, Amitabh ...
KDD
1998
ACM
102views Data Mining» more  KDD 1998»
15 years 4 months ago
Defining the Goals to Optimise Data Mining Performance
In many data mining problems the definition of what structures in the database are to be regarded as interesting or valuable is given only loosely. Typically this is regarded as a...
Mark G. Kelly, David J. Hand, Niall M. Adams
OPODIS
2008
15 years 1 months ago
Group Renaming
We study the group renaming problem, which is a natural generalization of the renaming problem. An instance of this problem consists of n processors, partitioned into m groups, ea...
Yehuda Afek, Iftah Gamzu, Irit Levy, Michael Merri...
SLSFS
2005
Springer
15 years 5 months ago
Random Projection, Margins, Kernels, and Feature-Selection
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...
Avrim Blum
COMBINATORICS
2006
92views more  COMBINATORICS 2006»
14 years 12 months ago
Equitable Matroids
One way to choose a basis of a matroid at random is to choose an ordering of the ground set uniformly at random and then use the greedy algorithm to find a basis. We investigate t...
Dillon Mayhew