:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Muller, Nadine, DeRosa, Stefano, Zhang, Su, Huan, Chun Lee
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2603.16881
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution
by: Lyu, Shen-Huan, et al.
Published: (2018)

Multi-Agent Reinforcement Learning for Task Offloading in Wireless Edge Networks
by: Fox, Andrea, et al.
Published: (2025)

Quantum-Evolutionary Neural Networks for Multi-Agent Federated Learning
by: Lala, Aarav, et al.
Published: (2025)

Multi-Agent Reinforcement Learning for Sample-Efficient Deep Neural Network Mapping
by: Krishnan, Srivatsan, et al.
Published: (2025)

Visualizing, Rethinking, and Mining the Loss Landscape of Deep Neural Networks
by: Xu, Yichu, et al.
Published: (2024)

Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks
by: Li, Xin-Chun, et al.
Published: (2024)

Communication-Aware Knowledge Distillation for Federated LLM Fine-Tuning over Wireless Networks
by: Zhang, Xinlu, et al.
Published: (2025)

Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-time Lightweight Time Series Anomaly Detection
by: Lee, Ming-Chang, et al.
Published: (2024)

Explaining Deep Neural Networks by Leveraging Intrinsic Methods
by: La Rosa, Biagio
Published: (2024)

Graph Neural Networks for Resource Allocation in Multi-Channel Wireless Networks
by: Chen, Lili, et al.
Published: (2025)

A Safe Deep Reinforcement Learning Approach for Energy Efficient Federated Learning in Wireless Communication Networks
by: Koursioumpas, Nikolaos, et al.
Published: (2023)

Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks
by: Lee, Su Hyeong, et al.
Published: (2025)

Lightweight Federated Learning over Wireless Edge Networks
by: Hou, Xiangwang, et al.
Published: (2025)

Intelligent Attacks and Defense Methods in Federated Learning-enabled Energy-Efficient Wireless Networks
by: Zhang, Han, et al.
Published: (2025)

Agent-Based Modeling and Deep Neural Networks for Establishing Digital Twins of Secure Facilities under Sensing Restrictions
by: Gunaratne, Chathika, et al.
Published: (2025)

Verified Safe Reinforcement Learning for Neural Network Dynamic Models
by: Wu, Junlin, et al.
Published: (2024)

Personalized Hierarchical Split Federated Learning in Wireless Networks
by: Pervej, Md-Ferdous, et al.
Published: (2024)

Revolutionizing Wireless Networks with Federated Learning: A Comprehensive Review
by: Mahdimahalleh, Sajjad Emdadi
Published: (2023)

Adaptive Federated Learning in Heterogeneous Wireless Networks with Independent Sampling
by: Geng, Jiaxiang, et al.
Published: (2024)

Partially Decentralized Multi-Agent Q-Learning via Digital Cousins for Wireless Networks
by: Bozkus, Talha, et al.
Published: (2025)

Mathematical Modeling and Convergence Analysis of Deep Neural Networks with Dense Layer Connectivities in Deep Learning
by: Huang, Jinshu, et al.
Published: (2025)

Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression
by: Shenouda, Joseph, et al.
Published: (2023)

Mixing Neural Networks and Exponential Moving Averages for Predicting Wireless Links Behavior
by: Formis, Gabriele, et al.
Published: (2024)

Topology of Out-of-Distribution Examples in Deep Neural Networks
by: Datta, Esha, et al.
Published: (2025)

WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks
by: Tong, Jingwen, et al.
Published: (2024)

Neural Network Learning and Quantum Gravity
by: Lanza, Stefano
Published: (2024)

Cooperative Edge Caching Based on Elastic Federated and Multi-Agent Deep Reinforcement Learning in Next-Generation Network
by: Wu, Qiong, et al.
Published: (2024)

Federated Learning over a Wireless Network: Distributed User Selection through Random Access
by: Sun, Chen, et al.
Published: (2023)

Quantitative CLTs in Deep Neural Networks
by: Favaro, Stefano, et al.
Published: (2023)

EMForecaster: A Deep Learning Framework for Time Series Forecasting in Wireless Networks with Distribution-Free Uncertainty Quantification
by: Mootoo, Xavier, et al.
Published: (2025)

Noise Resilient Over-The-Air Federated Learning In Heterogeneous Wireless Networks
by: Shaban, Zubair, et al.
Published: (2025)

Adaptive Decentralized Federated Learning in Energy and Latency Constrained Wireless Networks
by: Yan, Zhigang, et al.
Published: (2024)

A Multi-Agent Multi-Environment Mixed Q-Learning for Partially Decentralized Wireless Network Optimization
by: Bozkus, Talha, et al.
Published: (2024)

Bayesian Learning for Deep Neural Network Adaptation
by: Xie, Xurong, et al.
Published: (2020)

On the Stability of Neural Networks in Deep Learning
by: Delattre, Blaise
Published: (2025)

Fed-Listing: Federated Label Distribution Inference in Graph Neural Networks
by: Nakarmi, Suprim, et al.
Published: (2026)

Heterogeneous Resource Allocation with Multi-task Learning for Wireless Networks
by: Mitsiou, Nikos A., et al.
Published: (2025)

Asynchronous Multi-Model Dynamic Federated Learning over Wireless Networks: Theory, Modeling, and Optimization
by: Chang, Zhan-Lun, et al.
Published: (2023)

Federated Latent Factor Learning for Recovering Wireless Sensor Networks Signal with Privacy-Preserving
by: Yu, Chengjun, et al.
Published: (2025)

Adaptive Model Pruning and Personalization for Federated Learning over Wireless Networks
by: Liu, Xiaonan, et al.
Published: (2023)