Nonlinear data description with Principal Polynomial Analysis
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Recently, we introduced a simple variational bound on mutual information, that resolves some of the difficulties in the application of information theory to machine learning. Here we study a specific application to Gaussian channels. It is well known that ...
This article addresses 2-dimensional layout of high-dimensional biomedical datasets, which is useful for browsing them efficiently We employ the isomap technique, which is based on classical MDS (multi-dimensional scaling) but seeks to preserve the intrins ...
In this paper we investigate the use of a temporal extension of Independent Component Analysis (ICA) for the discrimination of three mental tasks for asynchronous EEG-based Brain Computer Interface systems. ICA is most commonly used with EEG for artifact i ...
This paper explores the issue of interactive low-dimensional human motion synthesis. We compare the performances of two motion models, i.e. Principal Components Analysis (PCA) or Probabilistic PCA (PPCA), for solving a constrained optimization problem with ...
This paper aims to propose a novel approach to generate new generic human walking patterns using motion-captured data, leading to a real-time engine intended for virtual humans animation. The method applies the PCA (principal component analysis) technique ...
We tested the hypothesis that common principles govern the production of the locomotor patterns for both straight-ahead and curved walking. Whole body movement recordings showed that continuous curved walking implies substantial, limb-specific changes in n ...
In this paper, we propose the use of (adaptive) nonlinear approximation for dimensionality reduction. In particular, we propose a dimensionality reduction method for learning a parts based representation of signals using redundant dictionaries. A redundant ...
In this paper we investigate the use of a temporal extension of Independent Component Analysis (ICA) for the discrimination of three mental tasks for asynchronous EEG-based Brain Computer Interface systems. ICA is most commonly used with EEG for artifact i ...
Geographic Information Science methods and tools are likely to help to extract useful and so far unknown information from large spatially explicit genetic datasets to understand the distribution of diversity among and within sheep and goat breeds. Consider ...
Joint experiments have been conducted on JET and DIII-D to study m = 2, n = I neo-classical tearing modes (NTMs). Very similar instability behaviour is observed on both machines and the scaling of the mode island width with beta and the observation of n = ...