38 citations · 81 across the 29 of their papers we have counts for
9 papers · 1 filter
Applying Opponent Modeling for Automatic Bidding in Online Repeated Auctions
Yudong Hu, Congying Han, Tiande Guo +1
Online auction scenarios, such as bidding searches on advertising platforms, often require bidders to participate repeatedly in auctions for identical or similar items. Most previo…
Generating Linear programming Instances with Controllable Rank and Condition Number
Anqi Li, Congying Han, Tiande Guo
Instances generation is crucial for linear programming algorithms, which is necessary either to find the optimal pivot rules by training learning method or to evaluate and verify c…
Masked Reconstruction Contrastive Learning with Information Bottleneck Principle
Ziwen Liu, Bonan Li, Congying Han +2
Contrastive learning (CL) has shown great power in self-supervised learning due to its ability to capture insight correlations among large-scale data. Current CL models are biased…
Comprehensive Analysis of Over-smoothing in Graph Neural Networks from Markov Chains Perspective
Weichen Zhao, Chenguang Wang, Congying Han +1
The over-smoothing problem is an obstacle of developing deep graph neural network (GNN). Although many approaches to improve the over-smoothing problem have been proposed, there is…
Generalized One-shot Domain Adaptation of Generative Adversarial Networks
Zicheng Zhang, Yinglu Liu, Congying Han +3
The adaptation of a Generative Adversarial Network (GAN) aims to transfer a pre-trained GAN to a target domain with limited training data. In this paper, we focus on the one-shot c…
NeuroPrim: An Attention-based Model for Solving NP-hard Spanning Tree Problems
Yuchen Shi, Congying Han, Tiande Guo
Spanning tree problems with specialized constraints can be difficult to solve in real-world scenarios, often requiring intricate algorithmic design and exponential time. Recently,…
On the optimal pivot path of simplex method for linear programming based on reinforcement learning
Anqi Li, Tiande Guo, Congying Han +2
Based on the existing pivot rules, the simplex method for linear programming is not polynomial in the worst case. Therefore the optimal pivot of the simplex method is crucial. This…
DropKey
Bonan Li, Yinhan Hu, Xuecheng Nie +4
In this paper, we focus on analyzing and improving the dropout technique for self-attention layers of Vision Transformer, which is important while surprisingly ignored by prior wor…
PetsGAN: Rethinking Priors for Single Image Generation
Zicheng Zhang, Yinglu Liu, Congying Han +3
Single image generation (SIG), described as generating diverse samples that have similar visual content with the given single image, is first introduced by SinGAN which builds a py…