Lagrangian relaxation is commonly used in combinatorial optimization to generate lower bounds for a minimization problem. We propose a modified Lagrangian relaxation which used i...
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
We show that the generating function (in n) for the number of walks on the square lattice with steps (1, 1), (1, −1), (2, 2) and (2, −2) from (0, 0) to (2n, 0) in the region 0...
Smoothly bent paper-like surfaces are developable. They are however difficult to minimally parameterize since the number of meaningful parameters is intrinsically dependent on the...
Abstract. We introduce an extension of Hoare logic for call-by-value higherorder functions with ML-like local reference generation. Local references may be generated dynamically an...