Search Results for author: Yan Jiao

Found 5 papers, 0 papers with code

Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning

no code implementations8 Mar 2021 Yan Jiao, Xiaocheng Tang, Zhiwei Qin, Shuaiji Li, Fan Zhang, Hongtu Zhu, Jieping Ye

We present a new practical framework based on deep reinforcement learning and decision-time planning for real-world vehicle repositioning on ride-hailing (a type of mobility-on-demand, MoD) platforms.

reinforcement-learning

Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem

no code implementations25 Nov 2019 John Holler, Risto Vuorio, Zhiwei Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye

Order dispatching and driver repositioning (also known as fleet management) in the face of spatially and temporally varying supply and demand are central to a ride-sharing platform marketplace.

Decision Making reinforcement-learning

CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms

no code implementations27 May 2019 Jiarui Jin, Ming Zhou, Wei-Nan Zhang, Minne Li, Zilong Guo, Zhiwei Qin, Yan Jiao, Xiaocheng Tang, Chenxi Wang, Jun Wang, Guobin Wu, Jieping Ye

How to optimally dispatch orders to vehicles and how to trade off between immediate and future returns are fundamental questions for a typical ride-hailing platform.

Multiagent Systems

Modeling of the Latent Embedding of Music using Deep Neural Network

no code implementations12 May 2017 Zhou Xing, Eddy Baik, Yan Jiao, Nilesh Kulkarni, Chris Li, Gautam Muralidhar, Marzieh Parandehgheibi, Erik Reed, Abhishek Singhal, Fei Xiao, Chris Pouliot

These latent embeddings can be used either as features to feed to subsequent models, such as collaborative filtering, or to build similarity metrics between songs, or to classify music based on the labels for training such as genre, mood, sentiment, etc.

Collaborative Filtering

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