activity
20192023
most citedField-wise Learning for Multi-field Categorical Data

4 citations · 10 across the 7 of their papers we have counts for

collaborators

8 papers

cs.SE2023★ 2 cited

Private-Library-Oriented Code Generation with Large Language Models

Daoguang Zan, Bei Chen, Yongshun Gong +6

Large language models (LLMs), such as Codex and GPT-4, have recently showcased their remarkable code generation abilities, facilitating a significant boost in coding efficiency. Th…

cs.SI2022

Latent Evolution Model for Change Point Detection in Time-varying Networks

Yongshun Gong, Xue Dong, Jian Zhang +1

Graph-based change point detection (CPD) play an irreplaceable role in discovering anomalous graphs in the time-varying network. While several techniques have been proposed to dete…

cs.LG2022

Exploring Linear Feature Disentanglement For Neural Networks

Tiantian He, Zhibin Li, Yongshun Gong +3

Non-linear activation functions, e.g., Sigmoid, ReLU, and Tanh, have achieved great success in neural networks (NNs). Due to the complex non-linear characteristic of samples, the o…

cs.CV2022

Series Photo Selection via Multi-view Graph Learning

Jin Huang, Lu Zhang, Yongshun Gong +3

Series photo selection (SPS) is an important branch of the image aesthetics quality assessment, which focuses on finding the best one from a series of nearly identical photos. Whil…

cs.LG2020★ 4 cited

Field-wise Learning for Multi-field Categorical Data

Zhibin Li, Jian Zhang, Yongshun Gong +2

We propose a new method for learning with multi-field categorical data. Multi-field categorical data are usually collected over many heterogeneous groups. These groups can reflect…

cs.LG2019★ 4 cited

Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development

Yongshun Gong, Zhibin Li, Jian Zhang +2

Recently, practical applications for passenger flow prediction have brought many benefits to urban transportation development. With the development of urbanization, a real-world de…