activity
20192025
most citedCross-Silo Federated Learning: Challenges and Opportunities

42 citations · 218 across the 44 of their papers we have counts for

collaborators
Showing cs.LGShow all

18 papers · 1 filter

cs.LG2025

Adventurer: Exploration with BiGAN for Deep Reinforcement Learning

Yongshuai Liu, Xin Liu

Recent developments in deep reinforcement learning have been very successful in learning complex, previously intractable problems. Sample efficiency and local optimality, however,…

cs.LG2023

Federated Linear Bandit Learning via Over-the-Air Computation

Jiali Wang, Yuning Jiang, Xin Liu +2

In this paper, we investigate federated contextual linear bandit learning within a wireless system that comprises a server and multiple devices. Each device interacts with the envi…

cs.LG2022★ 3 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.LG2022★ 2 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★ 14 cited

GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization

Xuhai Xu, Han Zhang, Yasaman Sefidgar +13

Recent research has demonstrated the capability of behavior signals captured by smartphones and wearables for longitudinal behavior modeling. However, there is a lack of a comprehe…

cs.LG2022★ 1 cited

ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs

Yujia Zhai, Chengquan Jiang, Leyuan Wang +5

Transformers have become keystone models in natural language processing over the past decade. They have achieved great popularity in deep learning applications, but the increasing…