42 citations · 63 across the 7 of their papers we have counts for
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cs.LG2023
Does Sparsity Help in Learning Misspecified Linear Bandits?
Jialin Dong, Lin F. Yang
Recently, the study of linear misspecified bandits has generated intriguing implications of the hardness of learning in bandits and reinforcement learning (RL). In particular, Du e…
cs.LG2021★ 1 cited
Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs
Jialin Dong, Da Zheng, Lin F. Yang +1
Graph neural networks (GNNs) are powerful tools for learning from graph data and are widely used in various applications such as social network recommendation, fraud detection, and…
cs.LG2020★ 9 cited
Faster Activity and Data Detection in Massive Random Access: A Multi-armed Bandit Approach
Jialin Dong, Jun Zhang, Yuanming Shi +1
This paper investigates the grant-free random access with massive IoT devices. By embedding the data symbols in the signature sequences, joint device activity detection and data de…