Sparse additive models are families of d-variate functions with the additive decomposition f∗ = ∑j∈S f∗ j , where S is an unknown subset of cardinality s d. In this paper,...
In this paper, we derive and evaluate theoretical ratedistortion performance bounds for scalable video compression algorithms which use a single motion-compensated prediction (MCP...
Gregory W. Cook, Josep Prades-Nebot, Edward J. Del...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
We consider derivative free methods based on sampling approaches for nonlinear optimization problems where derivatives of the objective function are not available and cannot be dir...
Methods for performing component matching by expressing an arithmetic specification and a bit-level description of an implementation as word-level polynomials have been demonstrat...