We present two results which arise from a model-based approach to hierarchical agglomerative clustering. First, we show formally that the common heuristic agglomerative clustering...
Sepandar D. Kamvar, Dan Klein, Christopher D. Mann...
Learning the structure of graphical models is an important task, but one of considerable difficulty when latent variables are involved. Because conditional independences using hid...
Recognizing a person’s motion is intuitive for humans but represents a challenging problem in machine vision. In this paper, we present a multi-disciplinary framework for recogn...
Crowdsourcing is an effective tool to solve hard tasks. By bringing 100,000s of people to work on simple tasks that only humans can do, we can go far beyond traditional models of ...
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...