Search Results for author: Jing Sun

Found 27 papers, 3 papers with code

Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem

no code implementations27 Feb 2024 Cong Zhang, Zhiguang Cao, Yaoxin Wu, Wen Song, Jing Sun

Existing learning-based methods for solving job shop scheduling problem (JSSP) usually use off-the-shelf GNN models tailored to undirected graphs and neglect the rich and meaningful topological structures of disjunctive graphs (DGs).

Graph Attention Job Shop Scheduling +1

State of Health Estimation for Battery Modules with Parallel-Connected Cells Under Cell-to-Cell Variations

no code implementations5 Dec 2023 Qinan Zhou, Dyche Anderson, Jing Sun

This paper proposes a new method and demonstrates that, with multiple features systematically selected from the module-level ICA and DVA, the module-level SOH can be estimated with high accuracy and confidence in the presence of cell-to-cell variations.

feature selection

Task-Specific Alignment and Multiple Level Transformer for Few-Shot Action Recognition

1 code implementation5 Jul 2023 Fei Guo, Li Zhu, YiWang Wang, Jing Sun

The second module (MLT) focuses on the Multiple-level feature of the support prototype and query sample to mine more information for the alignment, which operates on different level features.

Few-Shot action recognition Few Shot Action Recognition +1

MB-HGCN: A Hierarchical Graph Convolutional Network for Multi-behavior Recommendation

no code implementations19 Jun 2023 Mingshi Yan, Zhiyong Cheng, Jing Sun, Fuming Sun, Yuxin Peng

In this paper, we propose MB-HGCN, a novel multi-behavior recommendation model that uses a hierarchical graph convolutional network to learn user and item embeddings from coarse-grained on the global level to fine-grained on the behavior-specific level.

Collaborative Filtering Multi-Task Learning +1

Introduction of an intriguing approach for eletric current transformer on-site examining repairing

no code implementations17 Apr 2023 Yuxuan Chen, Jing Sun, Boqi Meng

However, due to the frequent occurrence of full current passing through the current transformer during use, its secondary winding has relatively more turns.

Decision-making with Speculative Opponent Models

no code implementations22 Nov 2022 Jing Sun, Shuo Chen, Cong Zhang, Yining Ma, Jie Zhang

To address this issue, we introduce Distributional Opponent-aided Multi-agent Actor-Critic (DOMAC), the first speculative opponent modelling algorithm that relies solely on local information (i. e., the controlled agent's observations, actions, and rewards).

Decision Making SMAC+ +1

Cascading Residual Graph Convolutional Network for Multi-Behavior Recommendation

1 code implementation26 May 2022 Mingshi Yan, Zhiyong Cheng, Chen Gao, Jing Sun, Fan Liu, Fuming Sun, Haojie Li

In particular, we design a cascading residual graph convolutional network structure, which enables our model to learn user preferences by continuously refining user embeddings across different types of behaviors.

Multi-Task Learning

Control Co-design of a Hydrokinetic Turbine with Open-loop Optimal Control

no code implementations3 Apr 2022 Boxi Jiang, Mohammad Reza Amini, Yingqian Liao, Joaquim R. R. A. Martins, Jing Sun

The optimization formulation incorporates a coupled dynamic-hydrodynamic model to maximize the rotor power efficiency for various time-variant flow profiles.

Energy-optimal Three-dimensional Path-following Control of Autonomous Underwater Vehicles under Ocean Currents

no code implementations22 Mar 2022 Niankai Yang, Chao Shen, Matthew Johnson-Roberson, Jing Sun

In the first stage, the surge velocity, heave velocity, and pitch angle setpoints are optimized by minimizing the required vehicle propulsion energy under currents, and the line-of-sight (LOS) guidance law is used to generate the yaw angle setpoint that ensures path following.

Eco-Coasting Strategies Using Road Grade Preview: Evaluation and Online Implementation Based on Mixed Integer Model Predictive Control

no code implementations14 Nov 2021 Yongjun Yan, Nan Li, Jinlong Hong, Bingzhao Gao, Hong Chen, Jing Sun, Ziyou Song

However, the comprehensive comparison between different coasting strategies and online performance of the eco-coasting strategy using road grade preview are still unclear because of the oversimplification and the integer variable in the optimal control problems.

Model Predictive Control

Artificial Neural Network and its Application Research Progress in Distillation

no code implementations1 Oct 2021 Jing Sun, Qi Tang

Artificial neural networks learn various rules and algorithms to form different ways of processing information, and have been widely used in various chemical processes.

Self-Learning

An Empirical Study on End-to-End Singing Voice Synthesis with Encoder-Decoder Architectures

no code implementations6 Aug 2021 Dengfeng Ke, Yuxing Lu, Xudong Liu, Yanyan Xu, Jing Sun, Cheng-Hao Cai

With the rapid development of neural network architectures and speech processing models, singing voice synthesis with neural networks is becoming the cutting-edge technique of digital music production.

Singing Voice Synthesis

Finite difference method for inhomogeneous fractional Dirichlet problem

no code implementations27 Jan 2021 Jing Sun, Weihua Deng, Daxin Nie

Based on this splitting, we respectively discretize the one- and two-dimensional integral fractional Laplacian with the inhomogeneous Dirichlet boundary condition and give the corresponding truncation errors with the help of the interpolation estimate.

Numerical Analysis Numerical Analysis

A Unified Joint Maximum Mean Discrepancy for Domain Adaptation

no code implementations25 Jan 2021 Wei Wang, Baopu Li, Shuhui Yang, Jing Sun, Zhengming Ding, Junyang Chen, Xiao Dong, Zhihui Wang, Haojie Li

From the revealed unified JMMD, we illustrate that JMMD degrades the feature-label dependence (discriminability) that benefits to classification, and it is sensitive to the label distribution shift when the label kernel is the weighted class conditional one.

Domain Adaptation

Robust State of Health Estimation of Lithium-ion Batteries Using Convolutional Neural Network and Random Forest

no code implementations20 Oct 2020 Niankai Yang, Ziyou Song, Heath Hofmann, Jing Sun

The challenge lies in the fact that partial discharge truncates the data available for SOH estimation, thereby leading to the loss or distortion of common SOH indicators.

Sparsely-Labeled Source Assisted Domain Adaptation

no code implementations8 May 2020 Wei Wang, Zhihui Wang, Yuankai Xiang, Jing Sun, Haojie Li, Fuming Sun, Zhengming Ding

However, there are usually a large number of unlabeled data but only a few labeled data in the source domain, and how to transfer knowledge from this sparsely-labeled source domain to the target domain is still a challenge, which greatly limits their application in the wild.

Clustering Domain Adaptation

aphBO-2GP-3B: A budgeted asynchronous parallel multi-acquisition functions for constrained Bayesian optimization on high-performing computing architecture

no code implementations20 Mar 2020 Anh Tran, Mike Eldred, Tim Wildey, Scott McCann, Jing Sun, Robert J. Visintainer

First, the efficiency of the Bayesian optimization is improved, where multiple input locations are evaluated massively parallel in an asynchronous manner to accelerate the optimization convergence with respect to physical runtime.

Bayesian Optimization Gaussian Processes

Importance Filtered Cross-Domain Adaptation

no code implementations24 Dec 2019 Wei Wang, Haojie Li, Zhihui Wang, Jing Sun, Zhengming Ding, Fuming Sun

Firstly, an importance filtered mechanism is devised to generate filtered soft labels to mitigate negative transfer desirably.

Domain Adaptation Object Recognition

Trainable back-propagated functional transfer matrices

1 code implementation28 Oct 2017 Cheng-Hao Cai, Yanyan Xu, Dengfeng Ke, Kaile Su, Jing Sun

In experiments, it is demonstrated that the revised rules can be used to train a range of functional connections: 20 different functions are applied to neural networks with up to 10 hidden layers, and most of them gain high test accuracies on the MNIST database.

The Impact of Road Configuration in V2V-based Cooperative Localization: Mathematical Analysis and Real-world Evaluation

no code implementations1 May 2017 Macheng Shen, Jing Sun, Ding Zhao

It has been shown, in our previous work, that the GNSS error can be reduced from several meters to sub-meter level by matching the biased GNSS positioning to a digital map with road constraints.

Systems and Control

Optimization of Vehicle Connections in V2V-based Cooperative Localization

no code implementations26 Mar 2017 Macheng Shen, Jing Sun, Ding Zhao

Cooperative map matching (CMM) uses the Global Navigation Satellite System (GNSS) positioning of a group of vehicles to improve the standalone localization accuracy.

Systems and Control

Improving Localization Accuracy in Connected Vehicle Networks Using Rao-Blackwellized Particle Filters: Theory, Simulations, and Experiments

no code implementations19 Feb 2017 Macheng Shen, Ding Zhao, Jing Sun, Huei Peng

A Rao-Blackwellized particle filter (RBPF) is used to jointly estimate the common biases of the pseudo-ranges and the vehicle positions.

Systems and Control

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