Search Results for author: Yijing Liu

Found 7 papers, 3 papers with code

MetaDD: Boosting Dataset Distillation with Neural Network Architecture-Invariant Generalization

no code implementations7 Oct 2024 Yunlong Zhao, Xiaoheng Deng, Xiu Su, Hongyan Xu, Xiuxing Li, Yijing Liu, Shan You

A significant challenge in DD is the dependency between the distilled dataset and the neural network (NN) architecture used.

Dataset Distillation

Fully Exploiting Every Real Sample: SuperPixel Sample Gradient Model Stealing

1 code implementation CVPR 2024 Yunlong Zhao, Xiaoheng Deng, Yijing Liu, Xinjun Pei, Jiazhi Xia, Wei Chen

With the basic idea of imitating the victim model's low-variance patch-level gradients instead of pixel-level gradients, SPSG achieves efficient sample gradient estimation through two steps.

Graph Diffusion Policy Optimization

1 code implementation26 Feb 2024 Yijing Liu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Wei Chen

Recent research has made significant progress in optimizing diffusion models for downstream objectives, which is an important pursuit in fields such as graph generation for drug design.

Drug Design Graph Generation

Using Terminal Circuit for Power System Electromagnetic Transient Simulation

no code implementations1 Jul 2021 Yijing Liu, Xiang Zhang, Renchang Dai, Guangyi Liu

The modern power system is evolving with increasing penetration of power electronics introducing complicated electromagnetic phenomenon.

Power System Transient Modeling and Simulation using Integrated Circuit

no code implementations6 Jun 2021 Xiang Zhang, Renchang Dai, Peng Wei, Yijing Liu, Guangyi Liu, Zhiwei Wang

Transient stability analysis (TSA) plays an important role in power system analysis to investigate the stability of power system.

Numerical Integration

GraphFederator: Federated Visual Analysis for Multi-party Graphs

no code implementations27 Aug 2020 Dongming Han, Wei Chen, Rusheng Pan, Yijing Liu, Jiehui Zhou, Ying Xu, Tianye Zhang, Changjie Fan, Jianrong Tao, Xiaolong, Zhang

This paper presents GraphFederator, a novel approach to construct joint representations of multi-party graphs and supports privacy-preserving visual analysis of graphs.

Human-Computer Interaction Cryptography and Security Graphics

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