Shiqiang Wang

Hans-Arno Jacobsen

CoRR, 2024

Hierarchical Federated Learning with Multi-Timescale Gradient Correction.

[BibT_eX]

[DOI]

CoRR, 2024

A Hierarchical Gradient Tracking Algorithm for Mitigating Subnet-Drift in Fog Learning Networks.

[BibT_eX]

[DOI]

Evan Chen

CoRR, 2024

Communication-Efficient Hybrid Federated Learning for E-health with Horizontal and Vertical Data Partitioning.

[BibT_eX]

[DOI]

CoRR, 2024

Federated Learning Priorities Under the European Union Artificial Intelligence Act.

[BibT_eX]

[DOI]

CoRR, 2024

Adaptive Model Pruning for Hierarchical Wireless Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE Wireless Communications and Networking Conference, 2024

Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates.

[BibT_eX]

[DOI]

Proceedings of the Twenty-fifth International Symposium on Theory, 2024

Active Learning for WBAN-based Health Monitoring.

[BibT_eX]

[DOI]

Proceedings of the Twenty-fifth International Symposium on Theory, 2024

FLEdge: Benchmarking Federated Learning Applications in Edge Computing Systems.

[BibT_eX]

[DOI]

Proceedings of the 25th International Middleware Conference, 2024

Erasure Coded Neural Network Inference via Fisher Averaging.

[BibT_eX]

[DOI]

Divyansh Jhunjhunwala

Neharika Jali

Proceedings of the IEEE International Symposium on Information Theory, 2024

Federated Learning While Providing Model as a Service: Joint Training and Inference Optimization.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2024, 2024

Taming Subnet-Drift in D2D-Enabled Fog Learning: A Hierarchical Gradient Tracking Approach.

[BibT_eX]

[DOI]

Evan Chen

Proceedings of the IEEE INFOCOM 2024, 2024

A Survey on Efficient Federated Learning Methods for Foundation Model Training.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

A New Theoretical Perspective on Data Heterogeneity in Federated Optimization.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging.

[BibT_eX]

[DOI]

Mingyue Ji

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Semantic Attribution for Explainable Uncertainty Quantification.

[BibT_eX]

[DOI]

Hanjing Wang

Qiang Ji

Proceedings of the Epistemic Uncertainty in Artificial Intelligence, 2024

Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly.

[BibT_eX]

[DOI]

Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning, 2024

FedFisher: Leveraging Fisher Information for One-Shot Federated Learning.

[BibT_eX]

[DOI]

Divyansh Jhunjhunwala

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Collaborative Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud Network.

[BibT_eX]

[DOI]

IEEE/ACM Trans. Netw., December, 2023

Model Pruning Enables Efficient Federated Learning on Edge Devices.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., December, 2023

Use Coupled LSTM Networks to Solve Constrained Optimization Problems.

[BibT_eX]

[DOI]

IEEE Trans. Cogn. Commun. Netw., April, 2023

Laplacian Matrix Sampling for Communication- Efficient Decentralized Learning.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., April, 2023

A Lightweight Method for Tackling Unknown Participation Probabilities in Federated Averaging.

[BibT_eX]

[DOI]

Mingyue Ji

CoRR, 2023

StableFDG: Style and Attention Based Learning for Federated Domain Generalization.

[BibT_eX]

[DOI]

Jaekyun Moon

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Technique to Solve Periodic Markov Decision Process for Network Resource Allocation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Military Communications Conference, 2023

Federated Learning with Flexible Control.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2023, 2023

LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

FedExP: Speeding Up Federated Averaging via Extrapolation.

[BibT_eX]

[DOI]

Divyansh Jhunjhunwala

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Incentive Mechanism Design for Unbiased Federated Learning with Randomized Client Participation.

[BibT_eX]

[DOI]

Proceedings of the 43rd IEEE International Conference on Distributed Computing Systems, 2023

Reinforcement Learning for Resource Allocation with Periodic Traffic Patterns.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Rethinking the Data Heterogeneity in Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022

Communication-Efficient $k$k-Means for Edge-Based Machine Learning.

[BibT_eX]

[DOI]

Stephen Pasteris

IEEE Trans. Parallel Distributed Syst., 2022

Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2022

A Survey on Federated Learning for Resource-Constrained IoT Devices.

[BibT_eX]

[DOI]

IEEE Internet Things J., 2022

Flexible Vertical Federated Learning with Heterogeneous Parties.

[BibT_eX]

[DOI]

Timothy Castiglia

Stacy Patterson

CoRR, 2022

Joint Coreset Construction and Quantization for Distributed Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2022

A Unified Analysis of Federated Learning with Arbitrary Client Participation.

[BibT_eX]

[DOI]

Mingyue Ji

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2022, 2022

Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2022, 2022

Sketch to Skip and Select: Communication Efficient Federated Learning Using Locality Sensitive Hashing.

[BibT_eX]

[DOI]

Georgios Kollias

Theodoros Salonidis

Proceedings of the Trustworthy Federated Learning - First International Workshop, 2022

Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Efficient Multi-Layer Stochastic Gradient Descent Algorithm for Federated Learning in E-health.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2022

Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

KerGNNs: Interpretable Graph Neural Networks with Graph Kernels.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Communication-Efficient Distributed Optimization Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Federated Learning, 2022

2021

Service Placement and Request Scheduling for Data-Intensive Applications in Edge Clouds.

[BibT_eX]

[DOI]

Konstantinos Poularakis

IEEE/ACM Trans. Netw., 2021

Guest Editorial: AI-Empowered Mobile Edge Computing in the Internet of Vehicles.

[BibT_eX]

[DOI]

IEEE Netw., 2021

Efficient deep learning.

[BibT_eX]

[DOI]

Nat. Comput. Sci., 2021

Cost-Effective Federated Learning in Mobile Edge Networks.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2021

Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning.

[BibT_eX]

[DOI]

Anirban Das

Stacy Patterson

CoRR, 2021

Robust Solutions to Constrained Optimization Problems by LSTM Networks.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE Military Communications Conference, 2021

PrivacyGuard: Enhancing Smart Home User Privacy.

[BibT_eX]

[DOI]

Proceedings of the IPSN '21: The 20th International Conference on Information Processing in Sensor Networks, 2021

Cost-Effective Federated Learning Design.

[BibT_eX]

[DOI]

Proceedings of the 40th IEEE Conference on Computer Communications, 2021

Tailored Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud System.

[BibT_eX]

[DOI]

Proceedings of the 40th IEEE Conference on Computer Communications, 2021

Robustness and Diversity Seeking Data-Free Knowledge Distillation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

Online Learning of Facility Locations.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 2021

2020

Looking Glass of NFV: Inferring the Structure and State of NFV Network From External Observations.

[BibT_eX]

[DOI]

IEEE/ACM Trans. Netw., 2020

Robust Coreset Construction for Distributed Machine Learning.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2020

Local Averaging Helps: Hierarchical Federated Learning and Convergence Analysis.

[BibT_eX]

[DOI]

CoRR, 2020

Sharing Models or Coresets: A Study based on Membership Inference Attack.

[BibT_eX]

[DOI]

CoRR, 2020

Federated Learning for Resource-Constrained IoT Devices: Panoramas and State-of-the-art.

[BibT_eX]

[DOI]

CoRR, 2020

Online Algorithms for Multi-shop Ski Rental with Machine Learned Predictions.

[BibT_eX]

[DOI]

Shufan Wang

Jian Li

CoRR, 2020

Data Selection for Federated Learning with Relevant and Irrelevant Data at Clients.

[BibT_eX]

[DOI]

CoRR, 2020

Capacity Analysis of Distributed Computing Systems with Multiple Resource Types.

[BibT_eX]

[DOI]

Pengchao Han

Kin K. Leung

Proceedings of the 2020 IEEE Wireless Communications and Networking Conference, 2020

Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice.

[BibT_eX]

[DOI]

Shufan Wang

Jian Li

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Joint Coreset Construction and Quantization for Distributed Machine Learning.

[BibT_eX]

[DOI]

Stephen Pasteris

Proceedings of the 2020 IFIP Networking Conference, 2020

Overcoming Noisy and Irrelevant Data in Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Communication-efficient k-Means for Edge-based Machine Learning.

[BibT_eX]

[DOI]

Stephen Pasteris

Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach.

[BibT_eX]

[DOI]

Pengchao Han

Ertugrul Necdet Ciftcioglu

Kin K. Leung

Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

Waypoint-based Topology Inference.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Communications, 2020

CoLearn: enabling federated learning in MUD-compliant IoT edge networks.

[BibT_eX]

[DOI]

Angelo Feraudo

Poonam Yadav

Vadim Safronov

Diana Andreea Popescu

Proceedings of the 3rd International Workshop on Edge Systems, Analytics and Networking, 2020

Detection of Anomalous Sounds for Machine Condition Monitoring using Classification Confidence.

[BibT_eX]

[DOI]

Tadanobu Inoue

Phongtharin Vinayavekhin

Proceedings of 5th the Workshop on Detection and Classification of Acoustic Scenes and Events 2020 (DCASE 2020), 2020

2019

Dynamic Service Migration in Mobile Edge Computing Based on Markov Decision Process.

[BibT_eX]

[DOI]

IEEE/ACM Trans. Netw., 2019

Investigating Statistical Privacy Frameworks from the Perspective of Hypothesis Testing.

[BibT_eX]

[DOI]

Proc. Priv. Enhancing Technol., 2019

Adaptive Federated Learning in Resource Constrained Edge Computing Systems.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2019

Model Pruning Enables Efficient Federated Learning on Edge Devices.

[BibT_eX]

[DOI]

CoRR, 2019

Robust Coreset Construction for Distributed Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2019

On Data Summarization for Machine Learning in Multi-organization Federations.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Smart Computing, 2019

Demonstration of Federated Learning in a Resource-Constrained Networked Environment.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Smart Computing, 2019

Acoustic anomaly detection system: demo abstract.

[BibT_eX]

[DOI]

Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 2019

Detection of Tennis Events from Acoustic Data.

[BibT_eX]

[DOI]

Proceedings of the Proceedings Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports, 2019

Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE Conference on Computer Communications, 2019

Service Placement and Request Scheduling for Data-intensive Applications in Edge Clouds.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE Conference on Computer Communications, 2019

Exact Incremental and Decremental Learning for LS-SVM.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Nocturnal Cough and Snore Detection in Noisy Environments Using Smartphone-Microphones.

[BibT_eX]

[DOI]

Sudip Vhaduri

Theodore G. van Kessel

Proceedings of the 2019 IEEE International Conference on Healthcare Informatics, 2019

Online Collection and Forecasting of Resource Utilization in Large-Scale Distributed Systems.

[BibT_eX]

[DOI]

Proceedings of the 39th IEEE International Conference on Distributed Computing Systems, 2019

Multicast-Based Weight Inference in General Network Topologies.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Communications, 2019

Shuffling and Mixing Data Augmentation for Environmental Sound Classification.

[BibT_eX]

[DOI]

Tadanobu Inoue

Phongtharin Vinayavekhin

Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events 2019 (DCASE 2019), 2019

MaxHedge: Maximizing a Maximum Online.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Live Service Migration in Mobile Edge Clouds.

[BibT_eX]

[DOI]

IEEE Wirel. Commun., 2018

Red/LeD: An Asymptotically Optimal and Scalable Online Algorithm for Service Caching at the Edge.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2018

MaxHedge: Maximising a Maximum Online with Theoretical Performance Guarantees.

[BibT_eX]

[DOI]

CoRR, 2018

When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Communications, 2018

Demo abstract: Distributed machine learning at resource-limited edge nodes.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2018, 2018

It's Hard to Share: Joint Service Placement and Request Scheduling in Edge Clouds with Sharable and Non-Sharable Resources.

[BibT_eX]

[DOI]

Proceedings of the 38th IEEE International Conference on Distributed Computing Systems, 2018

Distributed Machine Learning in Coalition Environments: Overview of Techniques.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Information Fusion, 2018

2017

Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs.

[BibT_eX]

[DOI]

IEEE Trans. Parallel Distributed Syst., 2017

Location Privacy in Mobile Edge Clouds: A Chaff-Based Approach.

[BibT_eX]

[DOI]

Ting He

IEEE J. Sel. Areas Commun., 2017

Online Placement of Multi-Component Applications in Edge Computing Environments.

[BibT_eX]

[DOI]

Murtaza Zafer

Kin K. Leung

IEEE Access, 2017

Data distribution and scheduling for distributed analytics tasks.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE SmartWorld, 2017

Location Privacy in Mobile Edge Clouds.

[BibT_eX]

[DOI]

Ting He

Ertugrul N. Ciftcioglu

Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

Non-negative matrix factorization of signals with overlapping events for event detection applications.

[BibT_eX]

[DOI]