15 papers
Long-Horizon Wireless Link Scheduling with State-Augmented Graph Neural Networks
Romina Garcia Camargo, Zhiyang Wang, Navid NaderiAlizadeh +1
We address optimal link scheduling in large-scale wireless networks. The goal is to schedule transmissions over a time horizon so that to maximize sum rate while ensuring that aver…
Efficient Transferable Optimal Transport via Min-Sliced Transport Plans
Xinran Liu, Elaheh Akbari, Rocio Diaz Martin +2
Optimal Transport (OT) offers a powerful framework for finding correspondences between distributions and addressing matching and alignment problems in various areas of computer vis…
LOTFormer: Doubly-Stochastic Linear Attention via Low-Rank Optimal Transport
Ashkan Shahbazi, Chayne Thrash, Yikun Bai +3
Transformers have proven highly effective across modalities, but standard softmax attention scales quadratically with sequence length, limiting long context modeling. Linear attent…
Decentralized Learning Strategies for Estimation Error Minimization with Graph Neural Networks
Xingran Chen, Navid NaderiAlizadeh, Alejandro Ribeiro +1
We address real-time sampling and estimation of autoregressive Markovian sources in dynamic yet structurally similar multi-hop wireless networks. Each node caches samples from othe…
Transferable Graphical MARL for Real-Time Estimation in Dynamic Wireless Networks
Xingran Chen, Navid NaderiAlizadeh, Alejandro Ribeiro +1
We study real-time sampling and estimation of autoregressive Markovian sources in decentralized and dynamic multi-hop networks that share similar structures. Nodes cache neighborin…
LUNA: Linear Universal Neural Attention with Generalization Guarantees
Ashkan Shahbazi, Ping He, Ali Abbasi +6
Scaling attention faces a critical bottleneck: the quadratic computational cost of softmax attention, which limits its application in long-sequence domains. Whil…