In the context of unsupervised learning, Lloyd's algorithm is one of the...
Dynamic treatment rules or policies are a sequence of decision functions...
State estimation in complex illumination environments based on conventio...
Multi-group data are commonly seen in practice. Such data structure cons...
The growing prevalence of tensor data, or multiway arrays, in science an...
We study the change point detection problem for high-dimensional linear
...
Considering the user mobility and unpredictable mobile edge computing (M...
We thank the opportunity offered by editors for this discussion and the
...
Recent development in data-driven decision science has seen great advanc...
Deep learning methods have achieved excellent performance in pose estima...
Domain adaptation (DA) aims at transferring knowledge from a labeled sou...
Recent years have witnessed significant progress in 3D hand mesh recover...
Hierarchical classification problems are commonly seen in practice. Howe...
Recent development in the data-driven decision science has seen great
ad...
The complexity of human cancer often results in significant heterogeneit...
This paper has two main goals: (a) establish several statistical
propert...
Insufficient labeled training datasets is one of the bottlenecks of 3D h...
Recent exploration of optimal individualized decision rules (IDRs) for
p...
With the emergence of precision medicine, estimating optimal individuali...
In variable selection, most existing screening methods focus on marginal...
Stability is an important aspect of a classification procedure because
u...
Gaussian graphical models are widely used to represent conditional depen...
Binary classification is a common statistical learning problem in which ...