Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...
Network traffic modeling generally views traffic as a superposition of flows that creates a timeseries of volume counts (e.g. of bytes or packets). What is omitted from this view ...
In this work we develop an approach for anomaly detection for large scale networks such as that of an enterprize or an ISP. The traffic patterns we focus on for analysis are that...
Spatial priors play crucial roles in many high-level vision tasks, e.g. scene understanding. Usually, learning spatial priors relies on training a structured output model. In this...
The purpose of this note is to describe the underlying insights and results obtained by the authors, and others, in a series of papers aimed at modelling the distribution of `natu...