9 papers
Target-Oriented Single Domain Generalization
Marzi Heidari, Yuhong Guo
Deep models trained on a single source domain often fail catastrophically under distribution shifts, a critical challenge in Single Domain Generalization (SDG). While existing meth…
Zero-Shot Action Generalization with Limited Observations
Abdullah Alchihabi, Hanping Zhang, Yuhong Guo
Reinforcement Learning (RL) has demonstrated remarkable success in solving sequential decision-making problems. However, in real-world scenarios, RL agents often struggle to genera…
Single Domain Generalization with Adversarial Memory
Hao Yan, Marzi Heidari, Yuhong Guo
Domain Generalization (DG) aims to train models that can generalize to unseen testing domains by leveraging data from multiple training domains. However, traditional DG methods rel…
A Unified Framework for Heterogeneous Semi-supervised Learning
Marzi Heidari, Abdullah Alchihabi, Hao Yan +1
In this work, we introduce a novel problem setup termed as Heterogeneous Semi-Supervised Learning (HSSL), which presents unique challenges by bridging the semi-supervised learning…
Single Domain Generalization with Model-aware Parametric Batch-wise Mixup
Marzi Heidari, Yuhong Guo
Single Domain Generalization (SDG) remains a formidable challenge in the field of machine learning, particularly when models are deployed in environments that differ significantly…
Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion
Abdullah Alchihabi, Yuhong Guo
Graph Neural Networks (GNNs) have demonstrated remarkable efficacy in tackling a wide array of graph-related tasks across diverse domains. However, a significant challenge lies in…