This paper proposes an adaptive penalized weighted mean regression for
o...
Based on binary inquiries, we developed an algorithm to estimate populat...
Traditional static functional data analysis is facing new challenges due...
Recognizing and telling similar objects apart is even hard for human bei...
Gaussian differential privacy (GDP) is a single-parameter family of priv...
Algorithmic fairness has received increased attention in socially sensit...
We consider the problem of learning a set of probability distributions f...
One of the major difficulties of reinforcement learning is learning from...
Distributional reinforcement learning (RL) is a class of state-of-the-ar...
In the functional linear regression model, many methods have been propos...
With widening deployments of natural language processing (NLP) in daily ...
Anderson mixing has been heuristically applied to reinforcement learning...
Distributional reinforcement learning (RL) is a class of state-of-the-ar...
Human activity recognition (HAR) based on mobile sensors plays an import...
In deep neural network, the cross-entropy loss function is commonly used...
The cqrReg package for R is the first to introduce a family of robust,
h...