In this paper, we propose a Thompson Sampling algorithm for unimodal
ban...
Optimization of deep learning algorithms to approach Nash Equilibrium re...
Stochastic Gradient Descent (SGD) has become the de facto way to train d...
Cloud GPU servers have become the de facto way for deep learning
practit...
Deep learning models are increasingly used for end-user applications,
su...
We consider the problem of learning to behave optimally in a Markov Deci...
In recent years significant progress has been made in dealing with
chall...
Off-policy reinforcement learning with eligibility traces is challenging...
Researchers on artificial intelligence have achieved human-level intelli...
Researchers on artificial intelligence have achieved human-level intelli...
Distributed training frameworks, like TensorFlow, have been proposed as ...
Recommendation systems and computing advertisements have gradually enter...
Algorithmic collusion is an emerging concept in current artificial
intel...