29 citations · 84 across the 14 of their papers we have counts for
14 papers
Generalizing Differentially Private Decentralized Deep Learning with Multi-Agent Consensus
Jasmine Bayrooti, Zhan Gao, Amanda Prorok
Cooperative decentralized learning relies on direct information exchange between communicating agents, each with access to locally available datasets. The goal is to agree on model…
Graph Neural Networks over the Air for Decentralized Tasks in Wireless Networks
Zhan Gao, Deniz Gunduz
Graph neural networks (GNNs) model representations from networked data and allow for decentralized inference through localized communications. Existing GNN architectures often assu…
Forward Inclusive Jet Productions in pA Collisions
Lei Wang, Lin Chen, Zhan Gao +3
Motivated by recent experimental LHC measurements on the forward inclusive jet productions and based on our previous calculations on forward hadron productions, we calculate single…
Learning Stable Graph Neural Networks via Spectral Regularization
Zhan Gao, Elvin Isufi
Stability of graph neural networks (GNNs) characterizes how GNNs react to graph perturbations and provides guarantees for architecture performance in noisy scenarios. This paper de…
Few-shot Fine-grained Image Classification via Multi-Frequency Neighborhood and Double-cross Modulation
Hegui Zhu, Zhan Gao, Jiayi Wang +2
Traditional fine-grained image classification typically relies on large-scale training samples with annotated ground-truth. However, some sub-categories have few available samples…
Learning Stochastic Graph Neural Networks with Constrained Variance
Zhan Gao, Elvin Isufi
Stochastic graph neural networks (SGNNs) are information processing architectures that learn representations from data over random graphs. SGNNs are trained with respect to the exp…
Wide and Deep Graph Neural Network with Distributed Online Learning
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Graph neural networks (GNNs) are naturally distributed architectures for learning representations from network data. This renders them suitable candidates for decentralized tasks.…
Spherical Convolutional Neural Networks: Stability to Perturbations in SO(3)
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Spherical convolutional neural networks (Spherical CNNs) learn nonlinear representations from 3D data by exploiting the data structure and have shown promising performance in shape…
Balancing Rates and Variance via Adaptive Batch-Size for Stochastic Optimization Problems
Zhan Gao, Alec Koppel, Alejandro Ribeiro
Stochastic gradient descent is a canonical tool for addressing stochastic optimization problems, and forms the bedrock of modern machine learning and statistics. In this work, we s…
Resource Allocation via Model-Free Deep Learning in Free Space Optical Communications
Zhan Gao, Mark Eisen, Alejandro Ribeiro
This paper investigates the general problem of resource allocation for mitigating channel fading effects in Free Space Optical (FSO) communications. The resource allocation problem…
Resource Allocation via Graph Neural Networks in Free Space Optical Fronthaul Networks
Zhan Gao, Mark Eisen, Alejandro Ribeiro
This paper investigates the optimal resource allocation in free space optical (FSO) fronthaul networks. The optimal allocation maximizes an average weighted sum-capacity subject to…
Wide and Deep Graph Neural Networks with Distributed Online Learning
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Graph neural networks (GNNs) learn representations from network data with naturally distributed architectures, rendering them well-suited candidates for decentralized learning. Oft…
Stochastic Graph Neural Networks
Zhan Gao, Elvin Isufi, Alejandro Ribeiro
Graph neural networks (GNNs) model nonlinear representations in graph data with applications in distributed agent coordination, control, and planning among others. Current GNN arch…
Optimal WDM Power Allocation via Deep Learning for Radio on Free Space Optics Systems
Zhan Gao, Mark Eisen, Alejandro Ribeiro
Radio on Free Space Optics (RoFSO), as a universal platform for heterogeneous wireless services, is able to transmit multiple radio frequency signals at high rates in free space op…