In applying Hidden Markov Models to the analysis of massive data streams, it is often necessary to use an artificially reduced set of states; this is due in large part to the fac...
Pedro F. Felzenszwalb, Daniel P. Huttenlocher, Jon...
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
This article introduces the concept of sensing dictionaries. It presents an alteration of greedy algorithms like thresholding or (Orthogonal) Matching Pursuit which improves their...
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...