Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
Abstract--S4 is a general-purpose, distributed, scalable, partially fault-tolerant, pluggable platform that allows programmers to easily develop applications for processing continu...
Leonardo Neumeyer, Bruce Robbins, Anish Nair, Anan...
With the increasing complexity of large-scale distributed (LSD) systems, an efficient monitoring mechanism has become an essential service for improving the performance and reliab...
Ehab S. Al-Shaer, Hussein M. Abdel-Wahab, Kurt Mal...
Scalability of object detectors with respect to the number of classes is a very important issue for applications where many object classes need to be detected. While combining sin...