5 citations · 18 across the 9 of their papers we have counts for
15 papers
A State-Augmented Approach for Learning Optimal Resource Management Decisions in Wireless Networks
Yiğit Berkay Uslu, Navid NaderiAlizadeh, Mark Eisen +1
We consider a radio resource management (RRM) problem in a multi-user wireless network, where the goal is to optimize a network-wide utility function subject to constraints on the…
Federated Representation Learning via Maximal Coding Rate Reduction
Juan Cervino, Navid NaderiAlizadeh, Alejandro Ribeiro
We propose a federated methodology to learn low-dimensional representations from a dataset that is distributed among several clients. In particular, we move away from the commonly-…
Wireless Link Scheduling via Graph Representation Learning: A Comparative Study of Different Supervision Levels
Navid Naderializadeh
We consider the problem of binary power control, or link scheduling, in wireless interference networks, where the power control policy is trained using graph representation learnin…
Set Representation Learning with Generalized Sliced-Wasserstein Embeddings
Navid Naderializadeh, Soheil Kolouri, Joseph F. Comer +2
An increasing number of machine learning tasks deal with learning representations from set-structured data. Solutions to these problems involve the composition of permutation-equiv…
Contrastive Self-Supervised Learning for Wireless Power Control
Navid Naderializadeh
We propose a new approach for power control in wireless networks using self-supervised learning. We partition a multi-layer perceptron that takes as input the channel matrix and ou…
Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning
Navid Naderializadeh, Fan H. Hung, Sean Soleyman +1
We propose a novel framework for value function factorization in multi-agent deep reinforcement learning (MARL) using graph neural networks (GNNs). In particular, we consider the t…