An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
—This paper addresses the problem of joint linear transceiver design in the downlink of multiuser MIMO systems. We define the performance criterion as minimizing the maximal mea...
A successive refinement of a finite element grid provides a sequence of nested grids and hierarchy of nested finite element spaces as well as a natural hierarchical decompositio...
We present a method for decomposing a hypergraph with certain regularities into smaller hypergraphs. By applying this to the set of all canonical covers of a given set of functiona...
A systematic understanding of the decomposability structures in network utility maximization is key to both resource allocation and functionality allocation. It helps us obtain the...