4 citations · 4 across the 4 of their papers we have counts for
4 papers
SatDL: Jointly Optimizing Data Redistribution and Training for Satellite-Based Distributed Learning
Hao Wu, Kin Whye Chew, Yizhan Han +2
Satellite-based distributed learning promises to train machine-learning models directly in orbit using massive, globally dispersed sensor data, thereby avoiding large-scale data do…
High-Dimensional Sparse Data Low-rank Representation via Accelerated Asynchronous Parallel Stochastic Gradient Descent
Qicong Hu, Hao Wu
Data characterized by high dimensionality and sparsity are commonly used to describe real-world node interactions. Low-rank representation (LR) can map high-dimensional sparse (HDS…
Throughput and Link Utilization Improvement in Satellite Networks: A Learning-Enabled Approach
Hao Wu
Satellite networks provide communication services to global users with an uneven geographical distribution. In densely populated regions, Inter-satellite links (ISLs) often experie…
A Survey of Learned Indexes for the Multi-dimensional Space
Abdullah Al-Mamun, Hao Wu, Qiyang He +2
A recent research trend involves treating database index structures as Machine Learning (ML) models. In this domain, single or multiple ML models are trained to learn the mapping f…