Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
Abstract-- Affective information is vital for effective human-tohuman communication. Likewise, human-to-computer communication could be potentiated by an "affective barometer&...
Abdul Rehman Abbasi, Matthew N. Dailey, Nitin V. A...
In recent years, a few researchers have challenged past dogma and suggested methods (such as the IC algorithm) for inferring causal relationship among variables using steady state ...
Network tomography aims at inferring internal network characteristics based on measurements at the edge of the network. In loss tomography, in particular, the characteristic of in...
Athina Markopoulou, Christina Fragouli, Minas Gjok...