Increasingly significant variational effects present a great challenge for delivering desired clock skew reliably. Non-tree clock network has been recognized as a promising approac...
Abstract. We propose in this work a novel variational method for computing maps between surfaces by combining informative geometric features and regularizing forces including inver...
Arthur W. Toga, Jonathan H. Morra, Paul M. Thompso...
Sparsity is a desirable property in high dimensional learning. The 1-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity. Combining the...
Nonlinear ICA may not result in nonlinear blind source separation, since solutions to nonlinear ICA are highly non-unique. In practice, the nonlinearity in the data generation pro...
In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...