Search Results for author: Yunfei Chu

Found 7 papers, 3 papers with code

Knowledge Distillation of Transformer-based Language Models Revisited

no code implementations29 Jun 2022 Chengqiang Lu, Jianwei Zhang, Yunfei Chu, Zhengyu Chen, Jingren Zhou, Fei Wu, Haiqing Chen, Hongxia Yang

In the past few years, transformer-based pre-trained language models have achieved astounding success in both industry and academia.

Knowledge Distillation Language Modelling

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI

1 code implementation11 Nov 2021 Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang, Ziqi Tan, Kun Kuang, Chao Wu, Fei Wu, Jingren Zhou, Hongxia Yang

However, edge computing, especially edge and cloud collaborative computing, are still in its infancy to announce their success due to the resource-constrained IoT scenarios with very limited algorithms deployed.

Cloud Computing Edge-computing

Dynamic Sequential Graph Learning for Click-Through Rate Prediction

no code implementations26 Sep 2021 Yunfei Chu, xiaofu Chang, Kunyang Jia, Jingzhen Zhou, Hongxia Yang

In this paper, we propose a novel method, named Dynamic Sequential Graph Learning (DSGL), to enhance users or items' representations by utilizing collaborative information from the local sub-graphs associated with users or items.

Click-Through Rate Prediction Graph Learning +1

TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning

2 code implementations17 May 2021 Lu Wang, xiaofu Chang, Shuang Li, Yunfei Chu, Hui Li, Wei zhang, Xiaofeng He, Le Song, Jingren Zhou, Hongxia Yang

Secondly, on top of the proposed graph transformer, we introduce a two-stream encoder that separately extracts representations from temporal neighborhoods associated with the two interaction nodes and then utilizes a co-attentional transformer to model inter-dependencies at a semantic level.

Contrastive Learning Graph Learning +2

Inductive Granger Causal Modeling for Multivariate Time Series

no code implementations10 Feb 2021 Yunfei Chu, Xiaowei Wang, Jianxin Ma, Kunyang Jia, Jingren Zhou, Hongxia Yang

To bridge this gap, we propose an Inductive GRanger cAusal modeling (InGRA) framework for inductive Granger causality learning and common causal structure detection on multivariate time series, which exploits the shared commonalities underlying the different individuals.

Time Series Time Series Analysis

Granger Causal Structure Reconstruction from Heterogeneous Multivariate Time Series

no code implementations25 Sep 2019 Yunfei Chu, Xiaowei Wang, Chunyan Feng, Jianxin Ma, Jingren Zhou, Hongxia Yang

Granger causal structure reconstruction is an emerging topic that can uncover causal relationship behind multivariate time series data.

Time Series Time Series Analysis

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