The autoregressive HMM has been shown to provide efficient parameter estimation and high-quality synthesis, but in previous experiments decision trees derived from a non-autoregre...
We study hierarchical clustering schemes under an axiomatic view. We show that within this framework, one can prove a theorem analogous to one of J. Kleinberg (Kleinberg, 2002), i...
We analyze the capacity scaling laws of wireless networks where the spatial distribution of nodes over the network area exhibits a high degree of clustering. In particular we cons...
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
We study the online clustering problem where data items arrive in an online fashion. The algorithm maintains a clustering of data items into similarity classes. Upon arrival of v, ...