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  • Olof Barr
  • The Computer Science Journal of Moldova
  • 2005
We construct a modi ed perceptron algorithm that is deterministic, polynomial and also as fast as previous known algorithms. The algorithm runs in time O(mn log n log(1/ρ)), where m is the number of examples, n the number of dimensions and ρ is approximately the size of the margin. We also construct a non-deterministic modi ed perceptron algorithm running(More)
We show that a polynomial-time rescaling algorithm, in [5], for finding feasible solutions to linear programs, has flaws in its theoretical framework. With new estimates for the algorithm, we show that it indeed terminates in polynomial time. Also, we present a modification of the algorithm, where we suggest a data dependent way of choosing a rescaling(More)
Letf(n, H, 5) be the maximal number of edges in a graph with n vertices not containing a subgraph H compatible with a transition system X in the family of transition systems !T. Here we will use a family of transition systems X,, defined through local edge colourings. At each vertex the edge set is partitioned into parts containing no more than s+ 1 edges.(More)
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