H. Vincent Poor

Distributed Learning in Wireless Networks: Recent Progress and Future Challenges

2021 · arXiv (Cornell University)

The next-generation of wireless networks will enable many machine learning (ML) tools and applications to efficiently analyze various types of data collected by edge devices for inference, autonomy, and decision making purposes. However, due to …

Distributed Gradient Methods for Nonconvex Optimization: Local and\n Global Convergence Guarantees

2020 · arXiv (Cornell University)

The article discusses distributed gradient-descent algorithms for computing\nlocal and global minima in nonconvex optimization. For local optimization, we\nfocus on distributed stochastic gradient descent (D-SGD)--a simple\nnetwork-based variant of classical SGD. We discuss local minima convergence\nguarantees and …

Integrated Sensing and Communication for Edge Inference with End-to-End Multi-View Fusion

2024 · arXiv (Cornell University)

Integrated sensing and communication (ISAC) is a promising solution to accelerate edge inference via the dual use of wireless signals. However, this paradigm needs to minimize the inference error and latency under ISAC co-functionality interference, …

The Gaussian Primitive Discrete Time and Filtered Diamond Channel: Correlated Noise and Dirty-Paper Coding

2024 · IEEE Transactions on Communications

We investigate the primitive diamond relay channel model comprising Gaussian channels with identical frequency responses from the user to the relays and with lossless fronthaul links with a limited rate from the relays to the …