activity
20192022
most citedEfficient Path Prediction for Semi-Supervised and Weakly Supervised Hierarchical Text Classification

17 citations · 82 across the 21 of their papers we have counts for

collaborators

26 papers

cs.LG20223 cited

Rectified Pessimistic-Optimistic Learning for Stochastic Continuum-armed Bandit with Constraints

Hengquan Guo, Qi Zhu, Xin Liu

This paper studies the problem of stochastic continuum-armed bandit with constraints (SCBwC), where we optimize a black-box reward function subject to a black-box constraint…

cs.LG20222 cited

Complex Hyperbolic Knowledge Graph Embeddings with Fast Fourier Transform

Huiru Xiao, Xin Liu, Yangqiu Song +2

The choice of geometric space for knowledge graph (KG) embeddings can have significant effects on the performance of KG completion tasks. The hyperbolic geometry has been shown to…

cs.LG2022

Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment

Zixian Yang, Xin Liu, Lei Ying

Multi-armed bandit (MAB) is a classic model for understanding the exploration-exploitation trade-off. The traditional MAB model for recommendation systems assumes the user stays in…

cs.CV2022

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

Ren Yang, Radu Timofte, Meisong Zheng +75

This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…

cs.CV2022

Federated Remote Physiological Measurement with Imperfect Data

Xin Liu, Mingchuan Zhang, Ziheng Jiang +2

The growing need for technology that supports remote healthcare is being acutely highlighted by an aging population and the COVID-19 pandemic. In health-related machine learning ap…

cs.LG20228 cited

Behaviour-Diverse Automatic Penetration Testing: A Curiosity-Driven Multi-Objective Deep Reinforcement Learning Approach

Yizhou Yang, Xin Liu

Penetration Testing plays a critical role in evaluating the security of a target network by emulating real active adversaries. Deep Reinforcement Learning (RL) is seen as a promisi…