We show that it is possible to achieve the same accuracy, on average, as...
The measurement of progress using benchmarks evaluations is ubiquitous i...
The horseshoe prior is known to possess many desirable properties for
Ba...
The Weibull distribution, with shape parameter k>0 and scale parameter
λ...
The aim of this manuscript is to introduce the Bayesian minimum message
...
In this short note we derive a new bias-adjusted maximum likelihood esti...
Principal component analysis (PCA) is perhaps the most widely method for...
We demonstrate a simple connection between dictionary methods for time s...
Until recently, the most accurate methods for time series classification...
Time series classification (TSC) is the area of machine learning interes...
Time series classification (TSC) is the area of machine learning interes...
In this note, we develop a novel algorithm for generating random numbers...
This paper applies the minimum message length principle to inference of
...
Global-local shrinkage hierarchies are an important, recent innovation i...