Search Results for author: Jing Du

Found 11 papers, 1 papers with code

Joint Identifiability of Cross-Domain Recommendation via Hierarchical Subspace Disentanglement

no code implementations6 Apr 2024 Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu, Lina Yao

Such a failure may overlook the conditionality between two domains and how it contributes to latent factor disentanglement, leading to negative transfer when domains are weakly correlated.

Disentanglement Transfer Learning

Urban Drone Navigation: Autoencoder Learning Fusion for Aerodynamics

no code implementations13 Oct 2023 Jiaohao Wu, Yang Ye, Jing Du

Drones are vital for urban emergency search and rescue (SAR) due to the challenges of navigating dynamic environments with obstacles like buildings and wind.

Drone navigation Multi-Objective Reinforcement Learning +1

Distributional Domain-Invariant Preference Matching for Cross-Domain Recommendation

no code implementations4 Sep 2023 Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu, Lina Yao

Next, we aim to build distributional implicit matchings between the domain-level preferences of two domains.

Preference Mapping

Dynamic Clustering Transformer Network for Point Cloud Segmentation

no code implementations30 May 2023 Dening Lu, Jun Zhou, Kyle Yilin Gao, Dilong Li, Jing Du, Linlin Xu, Jonathan Li

Specifically, we propose novel semantic feature-based dynamic sampling and clustering methods in the encoder, which enables the model to be aware of local semantic homogeneity for local feature aggregation.

Clustering Decoder +2

Support Vector Machine Guided Reproducing Kernel Particle Method for Image-Based Modeling of Microstructures

no code implementations23 May 2023 Yanran Wang, Jonghyuk Baek, Yichun Tang, Jing Du, Mike Hillman, J. S. Chen

The proposed method modifies the smooth kernel functions with a regularized heavy-side function concerning the material interfaces to alleviate Gibb's oscillations.

Image Segmentation Semantic Segmentation

Improved Trust in Human-Robot Collaboration with ChatGPT

no code implementations25 Apr 2023 Yang Ye, Hengxu You, Jing Du

A human-subject experiment showed that incorporating ChatGPT in robots significantly increased trust in human-robot collaboration, which can be attributed to the robot's ability to communicate more effectively with humans.

Robot-Enabled Construction Assembly with Automated Sequence Planning based on ChatGPT: RoboGPT

no code implementations21 Apr 2023 Hengxu You, Yang Ye, Tianyu Zhou, Qi Zhu, Jing Du

To expand the ability of the current robot system in sequential understanding, this paper introduces RoboGPT, a novel system that leverages the advanced reasoning capabilities of ChatGPT, a large language model, for automated sequence planning in robot-based assembly applied to construction tasks.

Language Modelling Large Language Model

Adversarially Contrastive Estimation of Conditional Neural Processes

no code implementations23 Mar 2023 Zesheng Ye, Jing Du, Lina Yao

Conditional Neural Processes~(CNPs) formulate distributions over functions and generate function observations with exact conditional likelihoods.

IDNP: Interest Dynamics Modeling using Generative Neural Processes for Sequential Recommendation

no code implementations9 Aug 2022 Jing Du, Zesheng Ye, Lina Yao, Bin Guo, Zhiwen Yu

In this study, we address these concerns by learning (1) multi-scale representations of short-term interests; and (2) dynamics-aware representations of long-term interests.

Sequential Recommendation

Cross-Modal ASR Post-Processing System for Error Correction and Utterance Rejection

no code implementations10 Jan 2022 Jing Du, ShiLiang Pu, Qinbo Dong, Chao Jin, Xin Qi, Dian Gu, Ru Wu, Hongwei Zhou

Although modern automatic speech recognition (ASR) systems can achieve high performance, they may produce errors that weaken readers' experience and do harm to downstream tasks.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways

1 code implementation18 Mar 2020 Weikai Tan, Nannan Qin, Lingfei Ma, Ying Li, Jing Du, Guorong Cai, Ke Yang, Jonathan Li

Semantic segmentation of large-scale outdoor point clouds is essential for urban scene understanding in various applications, especially autonomous driving and urban high-definition (HD) mapping.

Autonomous Driving Scene Understanding +2

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