The brain produces feelings of confidence that inform decisions the same way statistics pulls patterns out of noisy data. This feeling of confidence is central to decision making, and, despite ample ...

Computational statistics harnesses the power of sophisticated numerical algorithms and high‐performance computing to solve complex inferential problems that are intractable by traditional analytical ...

This is a preview. Log in through your library . Abstract In recent years, sparse principal component analysis has emerged as an extremely popular dimension reduction technique for high-dimensional ...

The directions, which came via cell phone, were a little garbled, but as you understood them: "Turn left at the 3rd light and go straight; the restaurant will be on your right side." Ten minutes ago ...

Title: Computation-information gap in high-dimensional clustering. Abstract: We investigate the existence of a fundamental computation-information gap for the problem of clustering a mixture of ...

The demand for a professional labor force skilled in data analysis and statistical methods, alongside scientific computation and other applied mathematics techniques, and has grown tremendously over ...

The field of seismology has seen in recent times significant advances driven by more sophisticated sensing methods and big data. Equally important has been the continuous development of statistical ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

The SURVEYMEANS procedure uses the Taylor expansion method to estimate sampling errors of estimators based on complex sample designs. This method obtains a linear approximation for the estimator and ...