diff --git a/README.md b/README.md index 6363f86..5f96b2c 100644 --- a/README.md +++ b/README.md @@ -529,8 +529,8 @@ Federated Learning papers accepted by top ML(machine learning) conference and jo |Title | Affiliation | Venue | Year | Materials| | ------------------------------------------------------------ | ------------------------------------------------------------ | -------------- | ---- | ------------------------------------------------------------ | -|Stabilizing and Accelerating Federated Learning on Heterogeneous Data With Partial Client Participation | | TPAMI | 2025 | [PUB](https://ieeexplore.ieee.org/document/10696955) | -|Medical Federated Model With Mixture of Personalized and Shared Components | | TPAMI | 2025 | [PUB](https://ieeexplore.ieee.org/document/10697408) | +| Stabilizing and Accelerating Federated Learning on Heterogeneous Data With Partial Client Participation | | TPAMI | 2025 | [[PUB](https://ieeexplore.ieee.org/document/10696955)] | +| Medical Federated Model With Mixture of Personalized and Shared Components | | TPAMI | 2025 | [[PUB](https://ieeexplore.ieee.org/document/10697408)] | | One-shot Federated Learning via Synthetic Distiller-Distillate Communication | | NeurIPS | 2024 | [[PUB](https://openreview.net/forum?id=6292sp7HiE)] | | Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data | | NeurIPS | 2024 | [[PUB](https://openreview.net/forum?id=uO53206oLJ)] | | FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Discrepancy-Aware Aggregation | | NeurIPS | 2024 | [[PUB](https://openreview.net/forum?id=c3OZBJpN7M)] | @@ -1387,15 +1387,15 @@ Federated Learning papers accepted by top Secure conference and journal, Includi |Title | Affiliation | Venue | Year | Materials| | ------------------------------------------------------------ | ------------------------------------------------------------ | ----- | ---- | ------------------------------------------------------------ | -|Byzantine-Robust Decentralized Federated Learning | | CCS | 2024 | [PUB](https://dl.acm.org/doi/10.1145/3658644.3670307) | -|Not One Less: Exploring Interplay between User Profiles and Items in Untargeted Attacks against Federated Recommendation | | CCS | 2024 | [PUB](https://dl.acm.org/doi/10.1145/3658644.3670365) | -|Cross-silo Federated Learning with Record-level Personalized Differential Privacy. | | CCS | 2024 | [PUB](https://dl.acm.org/doi/10.1145/3658644.3670351) | -|Samplable Anonymous Aggregation for Private Federated Data Analysis | | CCS | 2024 | [PUB](https://dl.acm.org/doi/10.1145/3658644.3690224) | -|Camel: Communication-Efficient and Maliciously Secure Federated Learning in the Shuffle Model of Differential Privacy | | CCS | 2024 | [PUB](https://dl.acm.org/doi/10.1145/3658644.3690200) | -|Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses | | CCS | 2024 | [PUB](https://dl.acm.org/doi/10.1145/3658644.3690187) | -|Two-Tier Data Packing in RLWE-based Homomorphic Encryption for Secure Federated Learning. | | CCS | 2024 | [PUB](https://dl.acm.org/doi/10.1145/3658644.3690191) | -|Poster: Protection against Source Inference Attacks in Federated Learning using Unary Encoding and Shuffling. | | CCS | 2024 | [PUB](https://dl.acm.org/doi/10.1145/3658644.3691411) | -|Poster: End-to-End Privacy-Preserving Vertical Federated Learning using Private Cross-Organizational Data Collaboration. | | CCS | 2024 | [PUB](https://dl.acm.org/doi/10.1145/3658644.3691383) | +| Byzantine-Robust Decentralized Federated Learning | | CCS | 2024 | [[PUB](https://dl.acm.org/doi/10.1145/3658644.3670307)] | +| Not One Less: Exploring Interplay between User Profiles and Items in Untargeted Attacks against Federated Recommendation | | CCS | 2024 | [[PUB](https://dl.acm.org/doi/10.1145/3658644.3670365)] | +| Cross-silo Federated Learning with Record-level Personalized Differential Privacy. | | CCS | 2024 | [[PUB](https://dl.acm.org/doi/10.1145/3658644.3670351)] | +| Samplable Anonymous Aggregation for Private Federated Data Analysis | | CCS | 2024 | [[PUB](https://dl.acm.org/doi/10.1145/3658644.3690224)] | +| Camel: Communication-Efficient and Maliciously Secure Federated Learning in the Shuffle Model of Differential Privacy | | CCS | 2024 | [[PUB](https://dl.acm.org/doi/10.1145/3658644.3690200)] | +| Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses | | CCS | 2024 | [[PUB](https://dl.acm.org/doi/10.1145/3658644.3690187)] | +| Two-Tier Data Packing in RLWE-based Homomorphic Encryption for Secure Federated Learning. | | CCS | 2024 | [[PUB](https://dl.acm.org/doi/10.1145/3658644.3690191)] | +| Poster: Protection against Source Inference Attacks in Federated Learning using Unary Encoding and Shuffling. | | CCS | 2024 | [[PUB](https://dl.acm.org/doi/10.1145/3658644.3691411)] | +| Poster: End-to-End Privacy-Preserving Vertical Federated Learning using Private Cross-Organizational Data Collaboration. | | CCS | 2024 | [[PUB](https://dl.acm.org/doi/10.1145/3658644.3691383)] | | FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting | | NDSS | 2024 | [[PUB](https://www.ndss-symposium.org/ndss-paper/fp-fed-privacy-preserving-federated-detection-of-browser-fingerprinting/)] | | FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning | | NDSS | 2024 | [[PUB](https://www.ndss-symposium.org/ndss-paper/freqfed-a-frequency-analysis-based-approach-for-mitigating-poisoning-attacks-in-federated-learning/)] | | Automatic Adversarial Adaption for Stealthy Poisoning Attacks in Federated Learning | | NDSS | 2024 | [[PUB](https://www.ndss-symposium.org/ndss-paper/automatic-adversarial-adaption-for-stealthy-poisoning-attacks-in-federated-learning/)] | @@ -1497,10 +1497,10 @@ Federated Learning papers accepted by top CV(computer vision) conference and jou | Federated Fuzzy C-means with Schatten-p Norm Minimization | | MM | 2024 | [[PUB](https://doi.org/10.1145/3664647.3681557)] | | Towards Effective Federated Graph Anomaly Detection via Self-boosted Knowledge Distillation | | MM | 2024 | [[PUB](https://doi.org/10.1145/3664647.3681415)] | | Physics-Driven Spectrum-Consistent Federated Learning for Palmprint Verification | | IJCV | 2024 | [[PUB](https://link.springer.com/article/10.1007/s11263-024-02077-9)] | -| FedHide: Federated Learning by Hiding in the Neighbors | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-72897-6_23)] | -| FedVAD: Enhancing Federated Video Anomaly Detection with GPT-Driven Semantic Distillation | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-73668-1_14)] | -| FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-73195-2_20)] | -| Pick-a-Back: Selective Device-to-Device Knowledge Transfer in Federated Continual Learning | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-73030-6_10)] | +| FedHide: Federated Learning by Hiding in the Neighbors | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-72897-6_23)] | +| FedVAD: Enhancing Federated Video Anomaly Detection with GPT-Driven Semantic Distillation | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-73668-1_14)] | +| FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-73195-2_20)] | +| Pick-a-Back: Selective Device-to-Device Knowledge Transfer in Federated Continual Learning | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-73030-6_10)] | | Federated Learning with Local Openset Noisy Labels | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-72754-2_3)] | | FedTSA: A Cluster-Based Two-Stage Aggregation Method for Model-Heterogeneous Federated Learning. | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-73010-8_22)] | | Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection | | ECCV | 2024 | [[PUB](https://link.springer.com/chapter/10.1007/978-3-031-73004-7_11)] | diff --git a/data.yaml b/data.yaml index 235825b..5ebdae2 100644 --- a/data.yaml +++ b/data.yaml @@ -4073,6 +4073,19 @@ fl-in-top-ml-conference-and-journal: year: 4 materials: 60 body: + - title: Stabilizing and Accelerating Federated Learning on Heterogeneous Data With + Partial Client Participation + affiliation: '' + venue: TPAMI + year: '2025' + materials: + PUB: https://ieeexplore.ieee.org/document/10696955 + - title: Medical Federated Model With Mixture of Personalized and Shared Components + affiliation: '' + venue: TPAMI + year: '2025' + materials: + PUB: https://ieeexplore.ieee.org/document/10697408 - title: One-shot Federated Learning via Synthetic Distiller-Distillate Communication affiliation: '' venue: NeurIPS @@ -4625,8 +4638,8 @@ fl-in-top-ml-conference-and-journal: year: '2024' materials: PUB: https://openreview.net/forum?id=djGx0hucok - - title: '$\texttt{pfl-research}$: simulation framework for accelerating research - in Private Federated Learning' + - title: "$\texttt{pfl-research}$: simulation framework for accelerating research\ + \ in Private Federated Learning" affiliation: '' venue: NeurIPS year: '2024' @@ -10278,6 +10291,67 @@ fl-in-top-secure-conference-and-journal: year: 4 materials: 60 body: + - title: Byzantine-Robust Decentralized Federated Learning + affiliation: '' + venue: CCS + year: '2024' + materials: + PUB: https://dl.acm.org/doi/10.1145/3658644.3670307 + - title: 'Not One Less: Exploring Interplay between User Profiles and Items in Untargeted + Attacks against Federated Recommendation' + affiliation: '' + venue: CCS + year: '2024' + materials: + PUB: https://dl.acm.org/doi/10.1145/3658644.3670365 + - title: Cross-silo Federated Learning with Record-level Personalized Differential + Privacy. + affiliation: '' + venue: CCS + year: '2024' + materials: + PUB: https://dl.acm.org/doi/10.1145/3658644.3670351 + - title: Samplable Anonymous Aggregation for Private Federated Data Analysis + affiliation: '' + venue: CCS + year: '2024' + materials: + PUB: https://dl.acm.org/doi/10.1145/3658644.3690224 + - title: 'Camel: Communication-Efficient and Maliciously Secure Federated Learning + in the Shuffle Model of Differential Privacy' + affiliation: '' + venue: CCS + year: '2024' + materials: + PUB: https://dl.acm.org/doi/10.1145/3658644.3690200 + - title: Distributed Backdoor Attacks on Federated Graph Learning and Certified + Defenses + affiliation: '' + venue: CCS + year: '2024' + materials: + PUB: https://dl.acm.org/doi/10.1145/3658644.3690187 + - title: Two-Tier Data Packing in RLWE-based Homomorphic Encryption for Secure Federated + Learning. + affiliation: '' + venue: CCS + year: '2024' + materials: + PUB: https://dl.acm.org/doi/10.1145/3658644.3690191 + - title: 'Poster: Protection against Source Inference Attacks in Federated Learning + using Unary Encoding and Shuffling.' + affiliation: '' + venue: CCS + year: '2024' + materials: + PUB: https://dl.acm.org/doi/10.1145/3658644.3691411 + - title: 'Poster: End-to-End Privacy-Preserving Vertical Federated Learning using + Private Cross-Organizational Data Collaboration.' + affiliation: '' + venue: CCS + year: '2024' + materials: + PUB: https://dl.acm.org/doi/10.1145/3658644.3691383 - title: 'FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting' affiliation: '' venue: NDSS @@ -10866,6 +10940,33 @@ fl-in-top-cv-conference-and-journal: year: '2024' materials: PUB: https://link.springer.com/article/10.1007/s11263-024-02077-9 + - title: 'FedHide: Federated Learning by Hiding in the Neighbors' + affiliation: '' + venue: ECCV + year: '2024' + materials: + PUB: https://link.springer.com/chapter/10.1007/978-3-031-72897-6_23 + - title: 'FedVAD: Enhancing Federated Video Anomaly Detection with GPT-Driven Semantic + Distillation' + affiliation: '' + venue: ECCV + year: '2024' + materials: + PUB: https://link.springer.com/chapter/10.1007/978-3-031-73668-1_14 + - title: 'FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the + Power of Heterogeneous Clients' + affiliation: '' + venue: ECCV + year: '2024' + materials: + PUB: https://link.springer.com/chapter/10.1007/978-3-031-73195-2_20 + - title: 'Pick-a-Back: Selective Device-to-Device Knowledge Transfer in Federated + Continual Learning' + affiliation: '' + venue: ECCV + year: '2024' + materials: + PUB: https://link.springer.com/chapter/10.1007/978-3-031-73030-6_10 - title: Federated Learning with Local Openset Noisy Labels affiliation: '' venue: ECCV