3 citations · 4 across the 4 of their papers we have counts for
4 papers
Bi-Granularity Contrastive Learning for Post-Training in Few-Shot Scene
Ruikun Luo, Guanhuan Huang, Xiaojun Quan
The major paradigm of applying a pre-trained language model to downstream tasks is to fine-tune it on labeled task data, which often suffers instability and low performance when th…
Enhancing autonomy transparency: an option-centric rationale approach
Ruikun Luo, Na Du, X. Jessie Yang
While the advances in artificial intelligence and machine learning empower a new generation of autonomous systems for assisting human performance, one major concern arises from the…
A Workload Adaptive Haptic Shared Control Scheme for Semi-Autonomous Driving
Ruikun Luo, Yifan Weng, Yifan Wang +7
Haptic shared control is used to manage the control authority allocation between a human and an autonomous agent in semi-autonomous driving. Existing haptic shared control schemes,…
Multi-Task Regularization with Covariance Dictionary for Linear Classifiers
Fanyi Xiao, Ruikun Luo, Zhiding Yu
In this paper we propose a multi-task linear classifier learning problem called D-SVM (Dictionary SVM). D-SVM uses a dictionary of parameter covariance shared by all tasks to do mu…