Toward the third generation artificial intelligence
There have been two competing paradigms in artificial intelligence (AI) development ever
since its birth in 1956, ie, symbolism and connectionism (or sub-symbolism). While …
since its birth in 1956, ie, symbolism and connectionism (or sub-symbolism). While …
Machine learning on big data: Opportunities and challenges
Abstract Machine learning (ML) is continuously unleashing its power in a wide range of
applications. It has been pushed to the forefront in recent years partly owing to the advent of …
applications. It has been pushed to the forefront in recent years partly owing to the advent of …
Machine learning in drug design: Use of artificial intelligence to explore the chemical structure–biological activity relationship
The paper presents a comprehensive overview of the use of artificial intelligence (AI)
systems in drug design. Neural networks, which are one of the systems employed in AI, are …
systems in drug design. Neural networks, which are one of the systems employed in AI, are …
A survey of Monte Carlo methods for parameter estimation
Statistical signal processing applications usually require the estimation of some parameters
of interest given a set of observed data. These estimates are typically obtained either by …
of interest given a set of observed data. These estimates are typically obtained either by …
Analyzing the training processes of deep generative models
Among the many types of deep models, deep generative models (DGMs) provide a solution
to the important problem of unsupervised and semi-supervised learning. However, training …
to the important problem of unsupervised and semi-supervised learning. However, training …
Is there a role for statistics in artificial intelligence?
S Friedrich, G Antes, S Behr, H Binder… - Advances in Data …, 2022 - Springer
The research on and application of artificial intelligence (AI) has triggered a comprehensive
scientific, economic, social and political discussion. Here we argue that statistics, as an …
scientific, economic, social and political discussion. Here we argue that statistics, as an …
Dendritic neuron model trained by information feedback-enhanced differential evolution algorithm for classification
As the well-known McCulloch–Pitts neuron model has long been criticized to be
oversimplified, different algebra to formulate a single neuron model has received increasing …
oversimplified, different algebra to formulate a single neuron model has received increasing …
Small sample learning in big data era
As a promising area in artificial intelligence, a new learning paradigm, called Small Sample
Learning (SSL), has been attracting prominent research attention in the recent years. In this …
Learning (SSL), has been attracting prominent research attention in the recent years. In this …