Search Results for author: Pengcheng Xu

Found 11 papers, 2 papers with code

From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare

no code implementations15 Sep 2024 Ming Li, Pengcheng Xu, Junjie Hu, Zeyu Tang, Guang Yang

Federated learning holds great potential for enabling large-scale healthcare research and collaboration across multiple centres while ensuring data privacy and security are not compromised.

Federated Learning

InstructBrush: Learning Attention-based Instruction Optimization for Image Editing

no code implementations27 Mar 2024 Ruoyu Zhao, Qingnan Fan, Fei Kou, Shuai Qin, Hong Gu, Wei Wu, Pengcheng Xu, Mingrui Zhu, Nannan Wang, Xinbo Gao

Two key techniques are introduced into InstructBrush, Attention-based Instruction Optimization and Transformation-oriented Instruction Initialization, to address the limitations of the previous method in terms of inversion effects and instruction generalization.

Molecular De Novo Design through Transformer-based Reinforcement Learning

no code implementations9 Oct 2023 Pengcheng Xu, Tao Feng, Tianfan Fu, Siddhartha Laghuvarapu, Jimeng Sun

In contrast to the traditional RNN-based models, our proposed method exhibits superior performance in generating compounds predicted to be active against various biological targets, capturing long-term dependencies in the molecular structure sequence.

reinforcement-learning Reinforcement Learning

MIRACLE: Multi-task Learning based Interpretable Regulation of Autoimmune Diseases through Common Latent Epigenetics

no code implementations24 Jun 2023 Pengcheng Xu, Jinpu Cai, Yulin Gao, Ziqi Rong

DNA methylation is a crucial regulator of gene transcription and has been linked to various diseases, including autoimmune diseases and cancers.

Decoder Multi-Task Learning

Class Overwhelms: Mutual Conditional Blended-Target Domain Adaptation

1 code implementation3 Feb 2023 Pengcheng Xu, Boyu Wang, Charles Ling

We demonstrate that domain labels are not directly necessary for BTDA if categorical distributions of various domains are sufficiently aligned even facing the imbalance of domains and the label distribution shift of classes.

Blended-target Domain Adaptation Label shift of blended-target domain adaptation +1

When Source-Free Domain Adaptation Meets Learning with Noisy Labels

no code implementations31 Jan 2023 Li Yi, Gezheng Xu, Pengcheng Xu, Jiaqi Li, Ruizhi Pu, Charles Ling, A. Ian McLeod, Boyu Wang

We also prove that such a difference makes existing LLN methods that rely on their distribution assumptions unable to address the label noise in SFDA.

Learning with noisy labels Source-Free Domain Adaptation

Predicting Li-ion Battery Cycle Life with LSTM RNN

no code implementations8 Jul 2022 Pengcheng Xu, Yunfeng Lu

Efficient and accurate remaining useful life prediction is a key factor for reliable and safe usage of lithium-ion batteries.

HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation

1 code implementation4 May 2021 Qingcheng Xiao, Size Zheng, Bingzhe Wu, Pengcheng Xu, Xuehai Qian, Yun Liang

Second, the overall design space composed of HW/SW partitioning, hardware optimization, and software optimization is huge.

Bayesian Optimization Q-Learning

Coordinated Cyber-Attack Detection Model of Cyber-Physical Power System Based on the Operating State Data Link

no code implementations27 Feb 2021 Lei Wang, Pengcheng Xu, Zhaoyang Qu, Xiaoyong Bo, Yunchang Dong, Zhenming Zhang, Yang Li

Existing coordinated cyber-attack detection methods have low detection accuracy and efficiency and poor generalization ability due to difficulties dealing with unbalanced attack data samples, high data dimensionality, and noisy data sets.

Cyber Attack Detection

Wasserstein Distance Based Domain Adaptation for Object Detection

no code implementations18 Sep 2019 Pengcheng Xu, Prudhvi Gurram, Gene Whipps, Rama Chellappa

Prior approaches utilize adversarial training based on cross entropy between the source and target domain distributions to learn a shared feature mapping that minimizes the domain gap.

Object object-detection +2

A Directed Acyclic Graph Approach to Online Log Parsing

no code implementations12 Jun 2018 Pinjia He, Jieming Zhu, Pengcheng Xu, Zibin Zheng, Michael R. Lyu

A typical log-based system reliability management procedure is to first parse log messages because of their unstructured format; and apply data mining techniques on the parsed logs to obtain critical system behavior information.

Software Engineering

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