We consider in discrete time, a general class of sequential stochastic
d...
We study vectorial functions with maximal number of bent components in t...
Time series underwent the transition from statistics to deep learning, a...
We revisit the Thompson sampling algorithm to control an unknown linear
...
We consider the problem of controlling an unknown linear quadratic Gauss...
Deep reinforcement learning (DRL) has demonstrated impressive performanc...
Automated Vehicles require exhaustive testing in simulation to detect as...
We consider optimal control of an unknown multi-agent linear quadratic (...
Recent deep neural networks based techniques, especially those equipped ...
Regret analysis is challenging in Multi-Agent Reinforcement Learning (MA...
Model-based reinforcement learning methods typically learn models for
hi...
Pushing is a useful robotic capability for positioning and reorienting
o...
Learning effective embedding has been proved to be useful in many real-w...
In this paper, we construct three classes of strictly optimal
frequency-...
We study a general class of dynamic games with asymmetric information wh...
We study a general class of dynamic multi-agent decision problems with
a...
In this paper, we construct two generalized cyclotomic binary sequences ...
In recent years, bike-sharing systems have been deployed in many cities,...