6 citations · 9 across the 8 of their papers we have counts for
8 papers
Capturing Uncertainty in Human Motion for Representation Learning in Soccer
Yizhou Xu, Lars Bretzner, Tiesheng Wang +1
This paper presents a self-supervised representation learning framework for understanding 3D skeleton-based human motion in soccer, using future motion prediction as the learning o…
Continual Driving Policy Optimization with Closed-Loop Individualized Curricula
Haoyi Niu, Yizhou Xu, Xingjian Jiang +1
The safety of autonomous vehicles (AV) has been a long-standing top concern, stemming from the absence of rare and safety-critical scenarios in the long-tail naturalistic driving d…
Communication Load Balancing via Efficient Inverse Reinforcement Learning
Abhisek Konar, Di Wu, Yi Tian Xu +3
Communication load balancing aims to balance the load between different available resources, and thus improve the quality of service for network systems. After formulating the load…
Policy Reuse for Communication Load Balancing in Unseen Traffic Scenarios
Yi Tian Xu, Jimmy Li, Di Wu +4
With the continuous growth in communication network complexity and traffic volume, communication load balancing solutions are receiving increasing attention. Specifically, reinforc…
(Re)H2O: Autonomous Driving Scenario Generation via Reversely Regularized Hybrid Offline-and-Online Reinforcement Learning
Haoyi Niu, Kun Ren, Yizhou Xu +4
Autonomous driving and its widespread adoption have long held tremendous promise. Nevertheless, without a trustworthy and thorough testing procedure, not only does the industry str…
Efficient Stein Variational Inference for Reliable Distribution-lossless Network Pruning
Yingchun Wang, Song Guo, Jingcai Guo +4
Network pruning is a promising way to generate light but accurate models and enable their deployment on resource-limited edge devices. However, the current state-of-the-art assumes…
Mitigating Spurious Correlations for Self-supervised Recommendation
Xinyu Lin, Yiyan Xu, Wenjie Wang +2
Recent years have witnessed the great success of self-supervised learning (SSL) in recommendation systems. However, SSL recommender models are likely to suffer from spurious correl…
Human Motion Prediction via Pattern Completion in Latent Representation Space
Yi Tian Xu, Yaqiao Li, David Meger
Inspired by ideas in cognitive science, we propose a novel and general approach to solve human motion understanding via pattern completion on a learned latent representation space.…