activity
20162024
most citedTeacher-Student Architecture for Knowledge Distillation: A Survey

13 citations · 26 across the 14 of their papers we have counts for

collaborators

14 papers

cs.NI2024

Probabilistic Mobility Load Balancing for Multi-band 5G and Beyond Networks

Saria Al Lahham, Di Wu, Ekram Hossain +2

The ever-increasing demand for data services and the proliferation of user equipment (UE) have resulted in a significant rise in the volume of mobile traffic. Moreover, in multi-ba…

cs.IR2023

Dual-space Hierarchical Learning for Goal-guided Conversational Recommendation

Can Chen, Hao Liu, Zeming Liu +2

Proactively and naturally guiding the dialog from the non-recommendation context (e.g., Chit-chat) to the recommendation scenario (e.g., Music) is crucial for the Conversational Re…

cs.LG2023

Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network

Fuyuan Lyu, Xing Tang, Dugang Liu +5

Deep sparse networks are widely investigated as a neural network architecture for prediction tasks with high-dimensional sparse features, with which feature interaction selection i…

cs.NI2023

Adaptive Dynamic Programming for Energy-Efficient Base Station Cell Switching

Junliang Luo, Yi Tian Xu, Di Wu +3

Energy saving in wireless networks is growing in importance due to increasing demand for evolving new-gen cellular networks, environmental and regulatory concerns, and potential en…

cs.CE2023

Parallel-mentoring for Offline Model-based Optimization

Can Chen, Christopher Beckham, Zixuan Liu +2

We study offline model-based optimization to maximize a black-box objective function with a static dataset of designs and scores. These designs encompass a variety of domains, incl…

cs.NI20232 cited

Realizing XR Applications Using 5G-Based 3D Holographic Communication and Mobile Edge Computing

Dun Yuan, Ekram Hossain, Di Wu +2

3D holographic communication has the potential to revolutionize the way people interact with each other in virtual spaces, offering immersive and realistic experiences. However, de…