Kamath, A.P., Karmarkar, N.K., Ramakrishnan, K.G., and Resende, M.G.C. (1991). A continous approach to inductive inference. Mathematical Programming, 57, 1992, 215-238.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....0 0 0.25 100 97.5 76.0 WalkSAT 0.5 100 98.2 62.6 0.75 100 90.5 19.4 0.25 93.1 2.8 0 Novelty 0.5 97.7 4.2 0 0.75 98.1 6.7 0 k term DNF learning problem to a satisfiability (SAT) problem and apply one of the many published SLS algorithms to the resulting SAT problem. In [13] Kamath et al. introduced a reduction of k term DNF learning to SAT. They generated a test set of 47 kterm DNF learning problem instances ranging from problems with eight variables up to 32 variables. The reduction of this test set to SAT has been widely used as a benchmark Note that this type ....

....of the problem setting space. Each test set contains one hundred soluble (for k=3) problem instances. The first test set was generated with = 10, n = 10, the second one with = 20, n = 42 and the third one with = 30, n = 180. We reduced the test sets to SAT using the reduction from [13]. The resulting SAT problems describe the desired solution F using 2 V ar k variables. They use another auxiliary variables to express, which positive example is covered by which term. The constraints put on those variables by the positive and negative examples are encoded in ( V ....

Kamath, A.P., Karmarkar, N.K., Ramakrishnan, K.G., and Resende, M.G.C. (1991). A continous approach to inductive inference. Mathematical Programming, 57, 1992, 215-238.

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Kamath, A.P., Karmarkar, N.K., Ramakrishnan, K.G., and Resende, M.G.C. (1991). A continous approach to inductive inference. Mathematical Programming, 57, 1992, 215-238.

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