Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Being non-invasive and effective at a distance, recognition suffers from low resolution sequence case. In this paper, we attempt to address the issue through the proposed high freq...
Junping Zhang, Jian Pu, Changyou Chen, Rudolf Flei...
In this paper, we present a model for unsupervised pattern discovery using non-negative matrix factorization (NMF) with graph regularization. Though the regularization can be appl...
Cortical recordings with high temporal resolution enable the tracking of neuronal excitation in response to stimuli. Here intra and extracranial recordings are analyzed from exper...
Janet M. Baker, Alexander M. Chan, Ksenija Marinko...
In this paper, a novel algorithm for bandwidth reduction in adaptive distributed learning is introduced. We deal with diffusion networks, in which the nodes cooperate with each ot...