60 citations · 329 across the 41 of their papers we have counts for
14 papers · 1 filter
Neuron with Steady Response Leads to Better Generalization
Qiang Fu, Lun Du, Haitao Mao +4
Regularization can mitigate the generalization gap between training and inference by introducing inductive bias. Existing works have already proposed various inductive biases from…
A Unified and Fast Interpretable Model for Predictive Analytics
Yuanyuan Jiang, Rui Ding, Tianchi Qiao +3
Predictive analytics aims to build machine learning models to predict behavior patterns and use predictions to guide decision-making. Predictive analytics is human involved, thus t…
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily
Lun Du, Xiaozhou Shi, Qiang Fu +4
Graph Neural Networks (GNNs) are widely used on a variety of graph-based machine learning tasks. For node-level tasks, GNNs have strong power to model the homophily property of gra…
ML4C: Seeing Causality Through Latent Vicinity
Haoyue Dai, Rui Ding, Yuanyuan Jiang +2
Supervised Causal Learning (SCL) aims to learn causal relations from observational data by accessing previously seen datasets associated with ground truth causal relations. This pa…
FORTAP: Using Formulas for Numerical-Reasoning-Aware Table Pretraining
Zhoujun Cheng, Haoyu Dong, Ran Jia +4
Tables store rich numerical data, but numerical reasoning over tables is still a challenge. In this paper, we find that the spreadsheet formula, which performs calculations on nume…
Neuron Campaign for Initialization Guided by Information Bottleneck Theory
Haitao Mao, Xu Chen, Qiang Fu +3
Initialization plays a critical role in the training of deep neural networks (DNN). Existing initialization strategies mainly focus on stabilizing the training process to mitigate…