We propose a new approach to semi-supervised clustering that utilizes boosting to simultaneously learn both a similarity measure and a clustering of the data from given instancele...
We propose a novel, high-level model of human learning and cognition, based on association forming. The model configures any input data stream featuring a high incidence of repeti...
In this paper, we address the problem of 3D articulated multi-person tracking in busy street scenes from a moving, human-level observer. In order to handle the complexity of multi-...
Stephan Gammeter, Andreas Ess, Tobias Jaeggli, Kon...
We introduce a general-purpose learning machine that we call the Guaranteed Error Machine, or GEM, and two learning algorithms, a real GEM algorithm and an ideal GEM algorithm. Th...
Abstract— This paper provides a concise modeling and performance evaluation of the iSCSI storage area network (SAN) architecture and protocol. SANs play a key role in business co...