In this paper, we improve the performance of intra prediction and simplify mode decision procedure at the same time. For these works, we apply a statistical learning method such a...
This article introduces a regularized logistic discrimination method that is especially suited for discretized stochastic processes (such as periodograms, spectrograms, EEG curves...
Abstract For many centuries scientists have wondered how the human brain represents thoughts in terms of the underlying biology of neural activity. Philosophers, linguists, cogniti...
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...