In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
We consider the problem of multiple kernel learning (MKL), which can be formulated as a convex-concave problem. In the past, two efficient methods, i.e., Semi-Infinite Linear Prog...
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Abstract. We consider the problem of constructing a proxy-based overlay skeleton tree (POST) in the backbone service domain of a two-tier overlay multicast infrastructure. Spanning...
Multicasting is one of the most important applications in Wireless Ad hoc Networks and the currently emerging Wireless Mesh Networks. In such networks, interference due to the shar...