A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2012; you can also visit the original URL.
The file type is application/pdf
.
Primal sparse Max-margin Markov networks
2009
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '09
Max-margin Markov networks (M 3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M 3 N enjoys dual sparsity. However, the existing M 3 N formulation does not enjoy primal sparsity, which is a desirable property for selecting significant features and reducing the risk of over-fitting. In this paper, we present an 1-norm regularized max-margin Markov network ( 1-M 3 N), which enjoys dual and primal sparsity simultaneously. To learn an
doi:10.1145/1557019.1557132
dblp:conf/kdd/ZhuXZ09
fatcat:4qj5ls34i5ahtbhokrt6mjlu5i