806 citations · 7.4k across the 169 of their papers we have counts for
14 papers · 1 filter
Reinforcement Learning for Caching with Space-Time Popularity Dynamics
Alireza Sadeghi, Georgios B. Giannakis, Gang Wang +1
With the tremendous growth of data traffic over wired and wireless networks along with the increasing number of rich-media applications, caching is envisioned to play a critical ro…
Learning Connectivity and Higher-order Interactions in Radial Distribution Grids
Qiuling Yang, Mario Coutino, Gang Wang +2
To perform any meaningful optimization task, distribution grid operators need to know the topology of their grids. Although power grid topology identification and verification has…
Deep Reinforcement Learning for Adaptive Caching in Hierarchical Content Delivery Networks
Alireza Sadeghi, Gang Wang, Georgios B. Giannakis
Caching is envisioned to play a critical role in next-generation content delivery infrastructure, cellular networks, and Internet architectures. By smartly storing the most popular…
Compressive Phase Retrieval via Reweighted Amplitude Flow
Liang Zhang, Gang Wang, Georgios B. Giannakis +1
The problem of reconstructing a sparse signal vector from magnitude-only measurements (a.k.a., compressive phase retrieval), emerges naturally in diverse applications, but it is NP…
Sparse Phase Retrieval via Truncated Amplitude Flow
Gang Wang, Liang Zhang, Georgios B. Giannakis +2
This paper develops a novel algorithm, termed \emph{SPARse Truncated Amplitude flow} (SPARTA), to reconstruct a sparse signal from a small number of magnitude-only measurements. It…
Solving Large-scale Systems of Random Quadratic Equations via Stochastic Truncated Amplitude Flow
Gang Wang, Georgios B. Giannakis, Jie Chen
A novel approach termed \emph{stochastic truncated amplitude flow} (STAF) is developed to reconstruct an unknown -dimensional real-/complex-valued signal from `phas…