38 citations · 81 across the 29 of their papers we have counts for
5 papers · 1 filter
A Game-Theoretic Approach for Improving Generalization Ability of TSP Solvers
Chenguang Wang, Yaodong Yang, Oliver Slumbers +4
In this paper, we introduce a two-player zero-sum framework between a trainable \emph{Solver} and a \emph{Data Generator} to improve the generalization ability of deep learning-bas…
ExSinGAN: Learning an Explainable Generative Model from a Single Image
ZiCheng Zhang, CongYing Han, TianDe Guo
Generating images from a single sample, as a newly developing branch of image synthesis, has attracted extensive attention. In this paper, we formulate this problem as sampling fro…
DFS: A Diverse Feature Synthesis Model for Generalized Zero-Shot Learning
Bonan Li, Xuecheng Nie, Congying Han
Generative based strategy has shown great potential in the Generalized Zero-Shot Learning task. However, it suffers severe generalization problem due to lacking of feature diversit…
Learning Graph Representation by Aggregating Subgraphs via Mutual Information Maximization
Chenguang Wang, Ziwen Liu
In this paper, we introduce a self-supervised learning method to enhance the graph-level representations with the help of a set of subgraphs. For this purpose, we propose a univers…
Blocked and Hierarchical Disentangled Representation From Information Theory Perspective
Ziwen Liu, Mingqiang Li, Congying Han
We propose a novel and theoretical model, blocked and hierarchical variational autoencoder (BHiVAE), to get better-disentangled representation. It is well known that information th…