In this work, we introduce an Interactive Parts (IP) model as an alternative to Hidden Markov Models (HMMs). We tested both models on a database of on-line cursive script. We show...
We propose a general framework for performing independent component analysis (ICA) which relies on ensemble learning and linear response theory known from statistical physics. We ...
We have developed a silicon neuron that is inspired by a mathematical model of the leech heartbeat (HN) interneuron. The temporal and ionic current behaviors of this silicon neuro...
Mario F. Simoni, Gennady S. Cymbalyuk, Michael E. ...
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
A central issue in principal component analysis (PCA) is choosing the number of principal components to be retained. By interpreting PCA as density estimation, this paper shows ho...