Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
Term weighting strongly influences the performance of text mining and information retrieval approaches. Usually term weights are determined through statistical estimates based on s...
In this paper we investigate how “self-awareness'', through on-line self-monitoring and measurement, coupled with intelligent adaptive behaviour in response to observe...
A constrained approximate dynamic programming (ADP) approach is presented for designing adaptive neural network (NN) controllers with closed-loop stability and performance guarante...
—We investigate optimal resource allocation and power management in virtualized data centers with time-varying workloads and heterogeneous applications. Prior work in this area u...
Rahul Urgaonkar, Ulas C. Kozat, Ken Igarashi, Mich...