8 citations · 20 across the 7 of their papers we have counts for
7 papers
Group-Agent Reinforcement Learning with Heterogeneous Agents
Kaiyue Wu, Xiao-Jun Zeng, Tingting Mu
Group-agent reinforcement learning (GARL) is a newly arising learning scenario, where multiple reinforcement learning agents study together in a group, sharing knowledge in an asyn…
LoopGaussian: Creating 3D Cinemagraph with Multi-view Images via Eulerian Motion Field
Jiyang Li, Lechao Cheng, Zhangye Wang +2
Cinemagraph is a unique form of visual media that combines elements of still photography and subtle motion to create a captivating experience. However, the majority of videos gener…
Understanding and Improving Ensemble Adversarial Defense
Yian Deng, Tingting Mu
The strategy of ensemble has become popular in adversarial defense, which trains multiple base classifiers to defend against adversarial attacks in a cooperative manner. Despite th…
Physics-Driven ML-Based Modelling for Correcting Inverse Estimation
Ruiyuan Kang, Tingting Mu, Panos Liatsis +1
When deploying machine learning estimators in science and engineering (SAE) domains, it is critical to avoid failed estimations that can have disastrous consequences, e.g., in aero…
Bi-directional Distribution Alignment for Transductive Zero-Shot Learning
Zhicai Wang, Yanbin Hao, Tingting Mu +3
It is well-known that zero-shot learning (ZSL) can suffer severely from the problem of domain shift, where the true and learned data distributions for the unseen classes do not mat…
Faster Riemannian Newton-type Optimization by Subsampling and Cubic Regularization
Yian Deng, Tingting Mu
This work is on constrained large-scale non-convex optimization where the constraint set implies a manifold structure. Solving such problems is important in a multitude of fundamen…