A great many computational algorithms developed over the past half-century have been
motivated or suggested by biological systems or processes, the most well-known being the …

This paper presents a comprehensive review of hybrid and ensemble-based soft computing
techniques applied to bankruptcy prediction. A variety of soft computing techniques are …

Accurate uncertainty quantification is a major challenge in deep learning, as neural
networks can make overconfident errors and assign high confidence predictions to out-of …

Bayesian optimization (BO) is a powerful approach for seeking the global optimum of
expensive black-box functions and has proven successful for fine tuning hyper-parameters …

The paper presents a new unsupervised dimensionality reduction technique, called
parametric t-SNE, that learns a parametric map** between the high-dimensional data …

We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series
analysis, with applications to learning models of human pose and motion from high …

WiFi localization, the task of determining the physical location of a mobile device from
wireless signal strengths, has been shown to be an accurate method of indoor and outdoor …

Cellular decision-making is mediated by a complex interplay of external stimuli with the
intracellular environment, in particular transcription factor regulatory networks. Here we have …

Images of facial expressions are often captured from various views as a result of either head
movements or variable camera position. Existing methods for multiview and/or view …

Interactive, task-guided character controllers must be agile and responsive to user input,
while retaining the flexibility to be readily authored and modified by the designer. Central to …