Network Programming
Network programming focuses on designing and implementing algorithms and architectures for processing information across interconnected nodes, aiming to efficiently solve complex computational problems. Current research emphasizes developing novel network architectures, such as graph neural networks and deep operator networks, and improving existing algorithms through techniques like frequency domain inference and tensor decomposition for faster and more accurate computations. These advancements are significant for diverse applications, including improved recommendation systems, enhanced anomaly detection in network flows, and more accurate causal inference from network data. The field's impact spans various scientific disciplines and practical applications, driving progress in areas like machine learning, signal processing, and social network analysis.
Papers
BeniFul: Backdoor Defense via Middle Feature Analysis for Deep Neural Networks
Xinfu Li, Junying Zhang, Xindi Ma
Implementing Derivations of Definite Logic Programs with Self-Attention Networks
Phan Thi Thanh Thuy, Akihiro Yamamoto
Advancing the Understanding of Fixed Point Iterations in Deep Neural Networks: A Detailed Analytical Study
Yekun Ke, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song
A Scalable Communication Protocol for Networks of Large Language Models
Samuele Marro, Emanuele La Malfa, Jesse Wright, Guohao Li, Nigel Shadbolt, Michael Wooldridge, Philip Torr
EasyRAG: Efficient Retrieval-Augmented Generation Framework for Automated Network Operations
Zhangchi Feng, Dongdong Kuang, Zhongyuan Wang, Zhijie Nie, Yaowei Zheng, Richong Zhang
Towards Bridging Generalization and Expressivity of Graph Neural Networks
Shouheng Li, Floris Geerts, Dongwoo Kim, Qing Wang
Towards characterizing the value of edge embeddings in Graph Neural Networks
Dhruv Rohatgi, Tanya Marwah, Zachary Chase Lipton, Jianfeng Lu, Ankur Moitra, Andrej Risteski
Scalable Weibull Graph Attention Autoencoder for Modeling Document Networks
Chaojie Wang, Xinyang Liu, Dongsheng Wang, Hao Zhang, Bo Chen, Mingyuan Zhou
LSTM-Based Proactive Congestion Management for Internet of Vehicle Networks
Aly Sabri Abdalla, Ahmad Al-Kabbany, Ehab F. Badran, Vuk Marojevic
GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks
Dingyi Zhuang, Chonghe Jiang, Yunhan Zheng, Shenhao Wang, Jinhua Zhao
PrivQuant: Communication-Efficient Private Inference with Quantized Network/Protocol Co-Optimization
Tianshi Xu, Shuzhang Zhong, Wenxuan Zeng, Runsheng Wang, Meng Li
DAWN: Designing Distributed Agents in a Worldwide Network
Zahra Aminiranjbar, Jianan Tang, Qiudan Wang, Shubha Pant, Mahesh Viswanathan
On the impact of key design aspects in simulated Hybrid Quantum Neural Networks for Earth Observation
Lorenzo Papa, Alessandro Sebastianelli, Gabriele Meoni, Irene Amerini