Spiking Neural Networks in Vertical Federated Learning: Performance Trade-offs
Fuente:
arXiv
Saved in:
| Main Authors: | Abbasihafshejani, Maryam, Maiti, Anindya, Jadliwala, Murtuza |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
VocalBridge: Latent Diffusion-Bridge Purification for Defeating Perturbation-Based Voiceprint Defenses
by: Abbasihafshejani, Maryam, et al.
Published: (2026)
by: Abbasihafshejani, Maryam, et al.
Published: (2026)
We Have a Package for You! A Comprehensive Analysis of Package Hallucinations by Code Generating LLMs
by: Spracklen, Joseph, et al.
Published: (2024)
by: Spracklen, Joseph, et al.
Published: (2024)
Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks
by: Kumari, Kavita, et al.
Published: (2024)
by: Kumari, Kavita, et al.
Published: (2024)
LLM Ghostbusters: Surgical Hallucination Suppression via Adaptive Unlearning
by: Spracklen, Joseph, et al.
Published: (2026)
by: Spracklen, Joseph, et al.
Published: (2026)
Learning Heterogeneous Performance-Fairness Trade-offs in Federated Learning
by: Ye, Rongguang, et al.
Published: (2025)
by: Ye, Rongguang, et al.
Published: (2025)
A Picture is Worth a Thousand Prompts? Efficacy of Iterative Human-Driven Prompt Refinement in Image Regeneration Tasks
by: Trinh, Khoi, et al.
Published: (2025)
by: Trinh, Khoi, et al.
Published: (2025)
Promptly Yours? A Human Subject Study on Prompt Inference in AI-Generated Art
by: Trinh, Khoi, et al.
Published: (2024)
by: Trinh, Khoi, et al.
Published: (2024)
Trading-off Accuracy and Communication Cost in Federated Learning
by: Villani, Mattia Jacopo, et al.
Published: (2025)
by: Villani, Mattia Jacopo, et al.
Published: (2025)
Privacy in Federated Learning with Spiking Neural Networks
by: Aksu, Dogukan, et al.
Published: (2025)
by: Aksu, Dogukan, et al.
Published: (2025)
Prompt and Circumstances: Evaluating the Efficacy of Human Prompt Inference in AI-Generated Art
by: Trinh, Khoi, et al.
Published: (2026)
by: Trinh, Khoi, et al.
Published: (2026)
Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)
by: Yang, Jirui, et al.
Published: (2024)
On the Sensitivity of Firing Rate-Based Federated Spiking Neural Networks to Differential Privacy
by: Pereira, Luiz, et al.
Published: (2026)
by: Pereira, Luiz, et al.
Published: (2026)
How Much is Too Much? Exploring LoRA Rank Trade-offs for Retaining Knowledge and Domain Robustness
by: Rathore, Darshita, et al.
Published: (2025)
by: Rathore, Darshita, et al.
Published: (2025)
A Bargaining-based Approach for Feature Trading in Vertical Federated Learning
by: Cui, Yue, et al.
Published: (2024)
by: Cui, Yue, et al.
Published: (2024)
Rethinking Spiking Neural Networks from an Ensemble Learning Perspective
by: Ding, Yongqi, et al.
Published: (2025)
by: Ding, Yongqi, et al.
Published: (2025)
Accuracy-Efficiency Trade-Offs in Spiking Neural Networks: A Lempel-Ziv Complexity Perspective on Learning Rules
by: Rudnicka, Zofia, et al.
Published: (2025)
by: Rudnicka, Zofia, et al.
Published: (2025)
The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning
by: Nguyen, Manh V., et al.
Published: (2024)
by: Nguyen, Manh V., et al.
Published: (2024)
Izhikevich-Inspired Temporal Dynamics for Enhancing Privacy, Efficiency, and Transferability in Spiking Neural Networks
by: Moshruba, Ayana, et al.
Published: (2025)
by: Moshruba, Ayana, et al.
Published: (2025)
Accuracy-Privacy Trade-off in the Mitigation of Membership Inference Attack in Federated Learning
by: Ahamed, Sayyed Farid, et al.
Published: (2024)
by: Ahamed, Sayyed Farid, et al.
Published: (2024)
Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
by: Xu, Qi, et al.
Published: (2025)
by: Xu, Qi, et al.
Published: (2025)
Chemical Reaction Networks Learn Better than Spiking Neural Networks
by: Jaffard, Sophie, et al.
Published: (2026)
by: Jaffard, Sophie, et al.
Published: (2026)
Towards Reliable Evaluation of Adversarial Robustness for Spiking Neural Networks
by: Wang, Jihang, et al.
Published: (2025)
by: Wang, Jihang, et al.
Published: (2025)
Characterizing Learning in Spiking Neural Networks with Astrocyte-Like Units
by: Yang, Christopher S., et al.
Published: (2025)
by: Yang, Christopher S., et al.
Published: (2025)
A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning
by: Zhang, Xiaojin, et al.
Published: (2024)
by: Zhang, Xiaojin, et al.
Published: (2024)
Dynamic Graph Structure Estimation for Learning Multivariate Point Process using Spiking Neural Networks
by: Chakraborty, Biswadeep, et al.
Published: (2025)
by: Chakraborty, Biswadeep, et al.
Published: (2025)
TreeCSS: An Efficient Framework for Vertical Federated Learning
by: Zhang, Qinbo, et al.
Published: (2024)
by: Zhang, Qinbo, et al.
Published: (2024)
Vertical Federated Learning in Practice: The Good, the Bad, and the Ugly
by: Wu, Zhaomin, et al.
Published: (2025)
by: Wu, Zhaomin, et al.
Published: (2025)
Unlearning Clients, Features and Samples in Vertical Federated Learning
by: Varshney, Ayush K., et al.
Published: (2025)
by: Varshney, Ayush K., et al.
Published: (2025)
VFLGAN: Vertical Federated Learning-based Generative Adversarial Network for Vertically Partitioned Data Publication
by: Yuan, Xun, et al.
Published: (2024)
by: Yuan, Xun, et al.
Published: (2024)
A Scalable, Causal, and Energy Efficient Framework for Neural Decoding with Spiking Neural Networks
by: Mentzelopoulos, Georgios, et al.
Published: (2025)
by: Mentzelopoulos, Georgios, et al.
Published: (2025)
On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis
by: Guan, Junyi, et al.
Published: (2025)
by: Guan, Junyi, et al.
Published: (2025)
FedEmb: A Vertical and Hybrid Federated Learning Algorithm using Network And Feature Embedding Aggregation
by: Meng, Fanfei, et al.
Published: (2023)
by: Meng, Fanfei, et al.
Published: (2023)
Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning
by: Osika, Zuzanna, et al.
Published: (2024)
by: Osika, Zuzanna, et al.
Published: (2024)
Tree-based Models for Vertical Federated Learning: A Survey
by: Qian, Bingchen, et al.
Published: (2025)
by: Qian, Bingchen, et al.
Published: (2025)
Spiking Neural Networks for Continuous Control via End-to-End Model-Based Learning
by: Huebotter, Justus, et al.
Published: (2025)
by: Huebotter, Justus, et al.
Published: (2025)
Bayesian Neural Network For Personalized Federated Learning Parameter Selection
by: Luo, Mengen, et al.
Published: (2024)
by: Luo, Mengen, et al.
Published: (2024)
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
by: Li, Yuecheng, et al.
Published: (2024)
by: Li, Yuecheng, et al.
Published: (2024)
Gradient-Free Continual Learning in Spiking Neural Networks via Inter-Spike Interval Regularization
by: Roy, Samrendra, et al.
Published: (2026)
by: Roy, Samrendra, et al.
Published: (2026)
TACOS: Task Agnostic Continual Learning in Spiking Neural Networks
by: Soures, Nicholas, et al.
Published: (2024)
by: Soures, Nicholas, et al.
Published: (2024)
Exploring Spiking Neural Networks for Binary Classification in Multivariate Time Series at the Edge
by: Ghawaly, James, et al.
Published: (2025)
by: Ghawaly, James, et al.
Published: (2025)
Similar Items
-
VocalBridge: Latent Diffusion-Bridge Purification for Defeating Perturbation-Based Voiceprint Defenses
by: Abbasihafshejani, Maryam, et al.
Published: (2026) -
We Have a Package for You! A Comprehensive Analysis of Package Hallucinations by Code Generating LLMs
by: Spracklen, Joseph, et al.
Published: (2024) -
Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks
by: Kumari, Kavita, et al.
Published: (2024) -
LLM Ghostbusters: Surgical Hallucination Suppression via Adaptive Unlearning
by: Spracklen, Joseph, et al.
Published: (2026) -
Learning Heterogeneous Performance-Fairness Trade-offs in Federated Learning
by: Ye, Rongguang, et al.
Published: (2025)