Ridesharing platforms are a type of two-sided marketplace where
“supply-...
A fundamental question in any peer-to-peer ride-sharing system is how to...
Recent works on ride-sharing order dispatching have highlighted the
impo...
Large ride-hailing platforms, such as DiDi, Uber and Lyft, connect tens ...
In this paper, we present a comprehensive, in-depth survey of the litera...
We present a new practical framework based on deep reinforcement learnin...
Reinforcement learning methods for traffic signal control has gained
inc...
Contextual multi-armed bandit (MAB) achieves cutting-edge performance on...
Order dispatching and driver repositioning (also known as fleet manageme...
Improving the efficiency of dispatching orders to vehicles is a research...
Similarity plays a fundamental role in many areas, including data mining...
Reinforcement learning aims at searching the best policy model for decis...
How to optimally dispatch orders to vehicles and how to trade off betwee...
Many applications require the collection of data on different variables ...
In this paper, we develop a reinforcement learning (RL) based system to ...
We consider classification tasks in the regime of scarce labeled trainin...
Robust tensor recovery plays an instrumental role in robustifying tensor...
We consider a class of sparse learning problems in high dimensional feat...