Search Results for author: Haizhou Du

Found 7 papers, 1 papers with code

A Unified Momentum-based Paradigm of Decentralized SGD for Non-Convex Models and Heterogeneous Data

no code implementations1 Mar 2023 Haizhou Du, Chengdong Ni

Emerging distributed applications recently boosted the development of decentralized machine learning, especially in IoT and edge computing fields.


Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings

no code implementations28 Oct 2022 Ryan Yang, Haizhou Du, Andre Wibisono, Patrick Baker

Distributed machine learning (DML) can be an important capability for modern military to take advantage of data and devices distributed at multiple vantage points to adapt and learn.

Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions

no code implementations29 Jan 2022 Haizhou Du, Ryan Yang, Yijian Chen, Qiao Xiang, Andre Wibisono, Wei Huang

In this paper, we analyze properties of the WPM and rigorously prove convergence properties of our aggregation mechanism.

Autonomous Driving

Vulcan: Solving the Steiner Tree Problem with Graph Neural Networks and Deep Reinforcement Learning

no code implementations21 Nov 2021 Haizhou Du, Zong Yan, Qiao Xiang, Qinqing Zhan

The core of Vulcan is a novel, compact graph embedding that transforms highdimensional graph structure data (i. e., path-changed information) into a low-dimensional vector representation.

Combinatorial Optimization Graph Embedding +3

Isomer: Transfer enhanced Dual-Channel Heterogeneous Dependency Attention Network for Aspect-based Sentiment Classification

no code implementations21 Nov 2021 Yukun Cao, Yijia Tang, Ziyue Wei, ChengKun Jin, Zeyu Miao, Yixin Fang, Haizhou Du, Feifei Xu

To solve those issues, we present a sentiment analysis model named Isomer, which performs a dual-channel attention on heterogeneous dependency graphs incorporating external knowledge, to effectively integrate other additional information.

Sentiment Analysis Sentiment Classification

Toward Efficient Federated Learning in Multi-Channeled Mobile Edge Network with Layerd Gradient Compression

no code implementations18 Sep 2021 Haizhou Du, Xiaojie Feng, Qiao Xiang, Haoyu Liu

Specifically, in LGC, local gradients from a device is coded into several layers and each layer is sent to the FL server along a different channel.

Federated Learning

Controllable Multi-Character Psychology-Oriented Story Generation

1 code implementation11 Oct 2020 Feifei Xu, Xinpeng Wang, Yunpu Ma, Volker Tresp, Yuyi Wang, Shanlin Zhou, Haizhou Du

In our work, we aim to design an emotional line for each character that considers multiple emotions common in psychological theories, with the goal of generating stories with richer emotional changes in the characters.

Story Generation

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