Search Results for author: Yu He

Found 20 papers, 6 papers with code

Beyond Emotion: A Multi-Modal Dataset for Human Desire Understanding

no code implementations NAACL 2022 Ao Jia, Yu He, Yazhou Zhang, Sagar Uprety, Dawei Song, Christina Lioma

Desire is a strong wish to do or have something, which involves not only a linguistic expression, but also underlying cognitive phenomena driving human feelings.


FedCAda: Adaptive Client-Side Optimization for Accelerated and Stable Federated Learning

no code implementations20 May 2024 Liuzhi Zhou, Yu He, Kun Zhai, Xiang Liu, Sen Liu, Xingjun Ma, Guangnan Ye, Yu-Gang Jiang, Hongfeng Chai

This comparative analysis revealed that due to the limited information contained within client models from other clients during the initial stages of federated learning, more substantial constraints need to be imposed on the parameters of the adaptive algorithm.

Federated Learning

Scalable Model Editing via Customized Expert Networks

1 code implementation3 Apr 2024 Zihan Yao, Yu He, Tianyu Qi, Ming Li

Our experiments on two different sizes of open-source large language models, the Llama2 7B and 13B, achieve state-of-the-art results compared to existing mainstream Model Editing methods.

Model Editing

Facility Location Games with Scaling Effects

no code implementations29 Feb 2024 Yu He, Alexander Lam, Minming Li

Consequently, we characterize the conditions on scaling functions which ensure that agents have single-peaked preferences.

Higher-Order Expander Graph Propagation

no code implementations14 Nov 2023 Thomas Christie, Yu He

To address this issue, recent works have explored using expander graphs, which are highly-connected sparse graphs with low diameters, to perform message passing.

VFLAIR: A Research Library and Benchmark for Vertical Federated Learning

1 code implementation15 Oct 2023 Tianyuan Zou, Zixuan Gu, Yu He, Hideaki Takahashi, Yang Liu, Ya-Qin Zhang

Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that allows participants with different features of the same group of users to accomplish cooperative training without exposing their raw data or model parameters.

Vertical Federated Learning

VMesh: Hybrid Volume-Mesh Representation for Efficient View Synthesis

no code implementations28 Mar 2023 Yuan-Chen Guo, Yan-Pei Cao, Chen Wang, Yu He, Ying Shan, XiaoHu Qie, Song-Hai Zhang

With the emergence of neural radiance fields (NeRFs), view synthesis quality has reached an unprecedented level.


Unsupervised Seismic Footprint Removal With Physical Prior Augmented Deep Autoencoder

no code implementations8 Feb 2023 Feng Qian, Yuehua Yue, Yu He, Hongtao Yu, Yingjie Zhou, Jinliang Tang, Guangmin Hu

Seismic acquisition footprints appear as stably faint and dim structures and emerge fully spatially coherent, causing inevitable damage to useful signals during the suppression process.

Continuous Neural Algorithmic Planners

no code implementations29 Nov 2022 Yu He, Petar Veličković, Pietro Liò, Andreea Deac

Neural algorithmic reasoning studies the problem of learning algorithms with neural networks, especially with graph architectures.

Continuous Control

ZOOMER: Boosting Retrieval on Web-scale Graphs by Regions of Interest

1 code implementation20 Mar 2022 Yuezihan Jiang, Yu Cheng, Hanyu Zhao, Wentao Zhang, Xupeng Miao, Yu He, Liang Wang, Zhi Yang, Bin Cui

We introduce ZOOMER, a system deployed at Taobao, the largest e-commerce platform in China, for training and serving GNN-based recommendations over web-scale graphs.


NeRFReN: Neural Radiance Fields with Reflections

no code implementations CVPR 2022 Yuan-Chen Guo, Di Kang, Linchao Bao, Yu He, Song-Hai Zhang

Specifically, we propose to split a scene into transmitted and reflected components, and model the two components with separate neural radiance fields.

Depth Estimation Novel View Synthesis

1.23-Tb/s per Wavelength Single-Waveguide On-Chip Optical Interconnect Enabled by Mode-division Multiplexing

no code implementations17 Oct 2020 Hanzi Huang, Yetian Huang, Yu He, Haoshuo Chen, Yong Zhang, Qianwu Zhang, Nicolas K. Fontaine, Roland Ryf, Yingxiong Song, Yikai Su

We experimentally demonstrate a record net capacity per wavelength of 1. 23~Tb/s over a single silicon-on-insulator (SOI) multimode waveguide for optical interconnects employing on-chip mode-division multiplexing and 11$\times$11 multiple-in-multiple-out (MIMO) digital signal processing.

RWNE: A Scalable Random-Walk-Based Network Embedding Framework with Personalized Higher-Order Proximity Preserved

1 code implementation18 Nov 2019 JianXin Li, Cheng Ji, Hao Peng, Yu He, Yangqiu Song, Xinmiao Zhang, Fanzhang Peng

However, despite the success of current random-walk-based methods, most of them are usually not expressive enough to preserve the personalized higher-order proximity and lack a straightforward objective to theoretically articulate what and how network proximity is preserved.

Network Embedding

A bi-diffusion based layer-wise sampling method for deep learning in large graphs

no code implementations25 Sep 2019 Yu He, Shiyang Wen, Wenjin Wu, Yan Zhang, Siran Yang, Yuan Wei, Di Zhang, Guojie Song, Wei Lin, Liang Wang, Bo Zheng

The Graph Convolutional Network (GCN) and its variants are powerful models for graph representation learning and have recently achieved great success on many graph-based applications.

Graph Representation Learning

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