16 citations · 54 across the 9 of their papers we have counts for
10 papers · 1 filter
A Unified Invariant Learning Framework for Graph Classification
Yongduo Sui, Jie Sun, Shuyao Wang +4
Invariant learning demonstrates substantial potential for enhancing the generalization of graph neural networks (GNNs) with out-of-distribution (OOD) data. It aims to recognize sta…
ALT: An Automatic System for Long Tail Scenario Modeling
Ya-Lin Zhang, Jun Zhou, Yankun Ren +5
In this paper, we consider the problem of long tail scenario modeling with budget limitation, i.e., insufficient human resources for model training stage and limited time and compu…
Interpretable MTL from Heterogeneous Domains using Boosted Tree
Ya-Lin Zhang, Longfei Li
Multi-task learning (MTL) aims at improving the generalization performance of several related tasks by leveraging useful information contained in them. However, in industrial scena…
SAFE: Scalable Automatic Feature Engineering Framework for Industrial Tasks
Qitao Shi, Ya-Lin Zhang, Longfei Li +3
Machine learning techniques have been widely applied in Internet companies for various tasks, acting as an essential driving force, and feature engineering has been generally recog…
A Time Attention based Fraud Transaction Detection Framework
Longfei Li, Ziqi Liu, Chaochao Chen +3
With online payment platforms being ubiquitous and important, fraud transaction detection has become the key for such platforms, to ensure user account safety and platform security…
Knowledge Consistency between Neural Networks and Beyond
Ruofan Liang, Tianlin Li, Longfei Li +2
This paper aims to analyze knowledge consistency between pre-trained deep neural networks. We propose a generic definition for knowledge consistency between neural networks at diff…