Search Results for author: Yuanyuan Li

Found 5 papers, 1 papers with code

Reinforcement Learning Approaches for the Orienteering Problem with Stochastic and Dynamic Release Dates

no code implementations2 Jul 2022 Yuanyuan Li, Claudia Archetti, Ivana Ljubic

In this paper, we study a sequential decision making problem faced by e-commerce carriers related to when to send out a vehicle from the central depot to serve customer requests, and in which order to provide the service, under the assumption that the time at which parcels arrive at the depot is stochastic and dynamic.

Decision Making reinforcement-learning +1

Revealing the CO2 emission reduction of ridesplitting and its determinants based on real-world data

no code implementations2 Apr 2022 Wenxiang Li, Yuanyuan Li, Ziyuan Pu, Long Cheng, Lei Wang, Linchuan Yang

Integrating the trip data with the COPERT model, this study calculates the CO2 emissions of shared rides (ridesplitting) and their substituted single rides (regular ridesourcing) to estimate the CO2 emission reduction of each ridesplitting trip.

Interpretable Machine Learning

RGB Image Classification with Quantum Convolutional Ansaetze

no code implementations23 Jul 2021 Yu Jing, Xiaogang Li, Yang Yang, Chonghang Wu, Wenbing Fu, Wei Hu, Yuanyuan Li, Hua Xu

With the rapid growth of qubit numbers and coherence times in quantum hardware technology, implementing shallow neural networks on the so-called Noisy Intermediate-Scale Quantum (NISQ) devices has attracted a lot of interest.

Classification Image Classification

Visual Semantic Reasoning for Image-Text Matching

2 code implementations ICCV 2019 Kunpeng Li, Yulun Zhang, Kai Li, Yuanyuan Li, Yun Fu

It outperforms the current best method by 6. 8% relatively for image retrieval and 4. 8% relatively for caption retrieval on MS-COCO (Recall@1 using 1K test set).

Cross-Modal Retrieval Image Retrieval +1

RUN:Residual U-Net for Computer-Aided Detection of Pulmonary Nodules without Candidate Selection

no code implementations30 May 2018 Tian Lan, Yuanyuan Li, Jonah Kimani Murugi, Yi Ding, Zhiguang Qin

The early detection and early diagnosis of lung cancer are crucial to improve the survival rate of lung cancer patients.

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