collaborators

11 papers

cs.LG2026

Generative Diffusion Models of Stochastic Graph Signals

Yiğit Berkay Uslu, Samar Hadou, Sergio Rozada +2

Sampling stochastic signals supported on a graph underlies many graph machine learning tasks, including recommender systems, forecasting in financial markets, and wireless network…

cs.CV2026

Active Sampling for Ultra-Low-Bit-Rate Video Compression via Conditional Controlled Diffusion

Amirhosein Javadi, Shirin Saeedi Bidokhti, Tara Javidi

Diffusion models provide a powerful generative prior for perceptual reconstruction at ultra-low bitrates, but effective video compression requires controlling the generative proces…

eess.SP2026

Graph Signal Diffusion Models for Wireless Resource Allocation

Yigit Berkay Uslu, Samar Hadou, Shirin Saeedi Bidokhti +1

We consider constrained ergodic resource optimization in wireless networks with graph-structured interference. We train a diffusion model policy to match expert conditional distrib…

eess.SY2026

Steering the Herd: A Framework for LLM-based Control of Social Learning

Raghu Arghal, Kevin He, Shirin Saeedi Bidokhti +1

Algorithms increasingly serve as information mediators--from social media feeds and targeted advertising to the increasing ubiquity of LLMs. This engenders a joint process where ag…

cs.LG2026

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…

eess.SP2026

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…