6 citations · 26 across the 12 of their papers we have counts for
7 papers · 1 filter
AuE-IPA: An AU Engagement Based Infant Pain Assessment Method
Mingze Sun, Haoxiang Wang, Wei Yao +1
Recent studies have found that pain in infancy has a significant impact on infant development, including psychological problems, possible brain injury, and pain sensitivity in adul…
Predicting Properties of Quantum Systems with Conditional Generative Models
Haoxiang Wang, Maurice Weber, Josh Izaac +1
Machine learning has emerged recently as a powerful tool for predicting properties of quantum many-body systems. For many ground states of gapped Hamiltonians, generative models ca…
Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems
Mao Ye, Ruichen Jiang, Haoxiang Wang +6
One of the key challenges of learning an online recommendation model is the temporal domain shift, which causes the mismatch between the training and testing data distribution and…
Asynchronous Training Schemes in Distributed Learning with Time Delay
Haoxiang Wang, Zhanhong Jiang, Chao Liu +3
In the context of distributed deep learning, the issue of stale weights or gradients could result in poor algorithmic performance. This issue is usually tackled by delay tolerant a…
Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond
Haoxiang Wang, Bo Li, Han Zhao
The vast majority of existing algorithms for unsupervised domain adaptation (UDA) focus on adapting from a labeled source domain to an unlabeled target domain directly in a one-off…
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning
Haoxiang Wang, Yite Wang, Ruoyu Sun +1
Model-agnostic meta-learning (MAML) and its variants have become popular approaches for few-shot learning. However, due to the non-convexity of deep neural nets (DNNs) and the bi-l…
Provable Domain Generalization via Invariant-Feature Subspace Recovery
Haoxiang Wang, Haozhe Si, Bo Li +1
Domain generalization asks for models trained over a set of training environments to perform well in unseen test environments. Recently, a series of algorithms such as Invariant Ri…