From 66e2f9d1192f2707d3fd932a14fdbbd99b127fa9 Mon Sep 17 00:00:00 2001 From: youngfish42 Date: Wed, 13 Dec 2023 23:15:31 +0800 Subject: [PATCH] auto update @ 2023-12-13T15:15:31Z Asia/Shanghai --- README.md | 72 +++++------ data.yaml | 358 +++++++++++++++++++++++++++++++++++++++++++++++------- 2 files changed, 351 insertions(+), 79 deletions(-) diff --git a/README.md b/README.md index 86dab6b..7d96062 100644 --- a/README.md +++ b/README.md @@ -438,8 +438,8 @@ Federated Learning papers accepted by top ML(machine learning) conference and jo | A First Look into the Carbon Footprint of Federated Learning | University of Cambridge | JMLR | 2023 | [[PUB](https://jmlr.org/papers/v24/21-0445.html)] [[PDF](https://arxiv.org/abs/2102.07627)] | | Attacks against Federated Learning Defense Systems and their Mitigation | The University of Newcastle | JMLR | 2023 | [[PUB](https://jmlr.org/papers/v24/22-0014.html)] [[CODE](https://github.com/codymlewis/viceroy)] | | A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates | Universit ́e Cˆ ote d’Azur | JMLR | 2023 | [[PUB](https://jmlr.org/papers/v24/22-0689.html)] [[PDF](https://arxiv.org/abs/2206.10189)] [[CODE](https://github.com/Accenture/Labs-Federated-Learning/tree/asynchronous_FL)] | -| Tighter Regret Analysis and Optimization of Online Federated Learning | Hanyang University | TPAMI | 2023 | [PUB](https://ieeexplore.ieee.org/document/10255290) [PDF](https://arxiv.org/abs/2205.06491) | -| Efficient Federated Learning Via Local Adaptive Amended Optimizer With Linear Speedup | University of Sydney | TPAMI | 2023 | PUB [PDF](https://arxiv.org/abs/2308.00522) | +| Tighter Regret Analysis and Optimization of Online Federated Learning | Hanyang University | TPAMI | 2023 | [[PUB](https://ieeexplore.ieee.org/document/10255290)] [[PDF](https://arxiv.org/abs/2205.06491)] | +| Efficient Federated Learning Via Local Adaptive Amended Optimizer With Linear Speedup | University of Sydney | TPAMI | 2023 | [[PDF](https://arxiv.org/abs/2308.00522)] | | Federated Learning Via Inexact ADMM. | BJTU | TPAMI | 2023 | [[PUB](https://ieeexplore.ieee.org/document/10040221)] [[PDF](https://arxiv.org/abs/2204.10607)] [[CODE](https://github.com/ShenglongZhou/FedADMM)] | | FedIPR: Ownership Verification for Federated Deep Neural Network Models | SJTU | TPAMI | 2023 | [[PUB](https://ieeexplore.ieee.org/document/9847383)] [[PDF](https://arxiv.org/abs/2109.13236)] [[CODE](https://github.com/purp1eHaze/FedIPR)] [[解读](https://zhuanlan.zhihu.com/p/562837170)] | | Decentralized Federated Averaging | NUDT | TPAMI | 2023 | [[PUB](https://ieeexplore.ieee.org/document/9850408)] [[PDF](https://arxiv.org/abs/2104.11375)] | @@ -825,12 +825,12 @@ Federated Learning papers accepted by top Secure conference and journal, Includi |Title | Affiliation | Venue | Year | Materials| | ------------------------------------------------------------ | ------------------------------------------------------------ | ----- | ---- | ------------------------------------------------------------ | -|Turning Privacy-preserving Mechanisms against Federated Learning | University of Pavia | CCS | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3576915.3623114) [PDF](https://arxiv.org/abs/2305.05355) | -|MESAS: Poisoning Defense for Federated Learning Resilient against Adaptive Attackers | University of Würzburg | CCS | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3576915.3623212) | -|martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecture | THU | CCS | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3576915.3623134) [PDF](https://arxiv.org/abs/2309.01098) [CODE](https://github.com/liqi16/martfl) | -|Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks | UIUC | CCS | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3576915.3623193) [PDF](https://arxiv.org/abs/2209.04030) | -|Poster: Verifiable Data Valuation with Strong Fairness in Horizontal Federated Learning | NSYSU | CCS | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3576915.3624371) | -|Poster: Bridging Trust Gaps: Data Usage Transparency in Federated Data Ecosystems | RWTH Aachen University | CCS | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3576915.3624371) | +| Turning Privacy-preserving Mechanisms against Federated Learning | University of Pavia | CCS | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3576915.3623114)] [[PDF](https://arxiv.org/abs/2305.05355)] | +| MESAS: Poisoning Defense for Federated Learning Resilient against Adaptive Attackers | University of Würzburg | CCS | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3576915.3623212)] | +| martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecture | THU | CCS | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3576915.3623134)] [[PDF](https://arxiv.org/abs/2309.01098)] [[CODE](https://github.com/liqi16/martfl)] | +| Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks | UIUC | CCS | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3576915.3623193)] [[PDF](https://arxiv.org/abs/2209.04030)] | +| Poster: Verifiable Data Valuation with Strong Fairness in Horizontal Federated Learning | NSYSU | CCS | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3576915.3624371)] | +| Poster: Bridging Trust Gaps: Data Usage Transparency in Federated Data Ecosystems | RWTH Aachen University | CCS | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3576915.3624371)] | | Every Vote Counts: Ranking-Based Training of Federated Learning to Resist Poisoning Attacks | University of Massachusetts Amherst | USENIX Security | 2023 | [[PUB](https://www.usenix.org/conference/usenixsecurity23/presentation/mozaffari)] [[PDF](https://arxiv.org/abs/2110.04350)] | | PrivateFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation | JHU | USENIX Security | 2023 | [[PUB](https://www.usenix.org/conference/usenixsecurity23/presentation/yang-yuchen)] [[CODE](https://github.com/BHui97/PrivateFL)] | | Gradient Obfuscation Gives a False Sense of Security in Federated Learning | NCSU | USENIX Security | 2023 | [[PUB](https://www.usenix.org/conference/usenixsecurity23/presentation/yue)] [[PDF](https://arxiv.org/abs/2206.04055)] [[CODE](https://github.com/KAI-YUE/rog)] | @@ -894,22 +894,22 @@ Federated Learning papers accepted by top CV(computer vision) conference and jou |Title | Affiliation | Venue | Year | Materials| | ------------------------------------------------------------ | ------------------------------------------------------------ | ----- | ---- | ------------------------------------------------------------ | -|FedCE: Personalized Federated Learning Method based on Clustering Ensembles | BJTU | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3612217) | -|FedVQA: Personalized Federated Visual Question Answering over Heterogeneous Scenes | Leiden University | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3611958) | -|Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor | XJTU | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3612597) [PDF](https://arxiv.org/abs/2312.02416) [CODE](https://github.com/J1nqianChen/FedKA) | -|Federated Deep Multi-View Clustering with Global Self-Supervision | UESTC | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3612027) [PDF](https://arxiv.org/abs/2309.13697) | -|FedAA: Using Non-sensitive Modalities to Improve Federated Learning while Preserving Image Privacy | ZJU | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3611953) | -|Prototype-guided Knowledge Transfer for Federated Unsupervised Cross-modal Hashing | SDNU | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3613837) [CODE](https://github.com/exquisite1210/PT-FUCH_P) | -|Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data | ZJU | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3612178) [PDF](https://arxiv.org/abs/2308.11646) | -|FedCD: A Classifier Debiased Federated Learning Framework for Non-IID Data | BUPT | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3611966) | -|Federated Learning with Label-Masking Distillation | UCAS | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3611984) [CODE](https://github.com/wnma3mz/FedLMD) | -|Cross-Silo Prototypical Calibration for Federated Learning with Non-IID Data | SDU | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3612481) [PDF](https://arxiv.org/abs/2308.03457) [CODE](https://github.com/qizhuang-qz/FedCSPC) | -|A Four-Pronged Defense Against Byzantine Attacks in Federated Learning | HUST | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3612474) [PDF](https://arxiv.org/abs/2308.03331) | -|Client-Adaptive Cross-Model Reconstruction Network for Modality-Incomplete Multimodal Federated Learning | CAS; Peng Cheng Laboratory; UCAS | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3611757) | -|FedGH: Heterogeneous Federated Learning with Generalized Global Header | NKU | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3611781) [PDF](https://arxiv.org/abs/2303.13137) [CODE](https://github.com/LipingYi/FedGH) | -|Cuing Without Sharing: A Federated Cued Speech Recognition Framework via Mutual Knowledge Distillation | CUHK | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3612134) [PDF](https://arxiv.org/abs/2308.03432) [CODE](https://github.com/yuxuanzhang0713/fedcsr) | -|AffectFAL: Federated Active Affective Computing with Non-IID Data | TJUT | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3612442) [CODE](https://github.com/AffectFAL/AffectFAL) | -|Improving Federated Person Re-Identification through Feature-Aware Proximity and Aggregation | SZU | MM | 2023 | [PUB](https://dl.acm.org/doi/10.1145/3581783.3612350) | +| FedCE: Personalized Federated Learning Method based on Clustering Ensembles | BJTU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612217)] | +| FedVQA: Personalized Federated Visual Question Answering over Heterogeneous Scenes | Leiden University | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3611958)] | +| Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor | XJTU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612597)] [[PDF](https://arxiv.org/abs/2312.02416)] [[CODE](https://github.com/J1nqianChen/FedKA)] | +| Federated Deep Multi-View Clustering with Global Self-Supervision | UESTC | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612027)] [[PDF](https://arxiv.org/abs/2309.13697)] | +| FedAA: Using Non-sensitive Modalities to Improve Federated Learning while Preserving Image Privacy | ZJU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3611953)] | +| Prototype-guided Knowledge Transfer for Federated Unsupervised Cross-modal Hashing | SDNU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3613837)] [[CODE](https://github.com/exquisite1210/PT-FUCH_P)] | +| Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data | ZJU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612178)] [[PDF](https://arxiv.org/abs/2308.11646)] | +| FedCD: A Classifier Debiased Federated Learning Framework for Non-IID Data | BUPT | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3611966)] | +| Federated Learning with Label-Masking Distillation | UCAS | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3611984)] [[CODE](https://github.com/wnma3mz/FedLMD)] | +| Cross-Silo Prototypical Calibration for Federated Learning with Non-IID Data | SDU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612481)] [[PDF](https://arxiv.org/abs/2308.03457)] [[CODE](https://github.com/qizhuang-qz/FedCSPC)] | +| A Four-Pronged Defense Against Byzantine Attacks in Federated Learning | HUST | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612474)] [[PDF](https://arxiv.org/abs/2308.03331)] | +| Client-Adaptive Cross-Model Reconstruction Network for Modality-Incomplete Multimodal Federated Learning | CAS; Peng Cheng Laboratory; UCAS | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3611757)] | +| FedGH: Heterogeneous Federated Learning with Generalized Global Header | NKU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3611781)] [[PDF](https://arxiv.org/abs/2303.13137)] [[CODE](https://github.com/LipingYi/FedGH)] | +| Cuing Without Sharing: A Federated Cued Speech Recognition Framework via Mutual Knowledge Distillation | CUHK | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612134)] [[PDF](https://arxiv.org/abs/2308.03432)] [[CODE](https://github.com/yuxuanzhang0713/fedcsr)] | +| AffectFAL: Federated Active Affective Computing with Non-IID Data | TJUT | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612442)] [[CODE](https://github.com/AffectFAL/AffectFAL)] | +| Improving Federated Person Re-Identification through Feature-Aware Proximity and Aggregation | SZU | MM | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3581783.3612350)] | | Towards Attack-tolerant Federated Learning via Critical Parameter Analysis | KAIST | ICCV | 2023 | [[PUB](https://openaccess.thecvf.com/content/ICCV2023/html/Han_Towards_Attack-tolerant_Federated_Learning_via_Critical_Parameter_Analysis_ICCV_2023_paper.html)] [[PDF](http://arxiv.org/abs/2308.09318)] [[CODE](https://github.com/Sungwon-Han/FEDCPA)] [[SUPP](https://openaccess.thecvf.com/content/ICCV2023/supplemental/Han_Towards_Attack-tolerant_Federated_ICCV_2023_supplemental.pdf)] | | Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation | NTU; NVIDIA | ICCV | 2023 | [[PUB](https://openaccess.thecvf.com/content/ICCV2023/html/Yang_Efficient_Model_Personalization_in_Federated_Learning_via_Client-Specific_Prompt_Generation_ICCV_2023_paper.html)] [[PDF](https://arxiv.org/abs/2308.15367)] [[SUPP](https://openaccess.thecvf.com/content/ICCV2023/supplemental/Yang_Efficient_Model_Personalization_ICCV_2023_supplemental.pdf)] | | Generative Gradient Inversion via Over-Parameterized Networks in Federated Learning | A*STAR | ICCV | 2023 | [[PUB](https://openaccess.thecvf.com/content/ICCV2023/html/Zhang_Generative_Gradient_Inversion_via_Over-Parameterized_Networks_in_Federated_Learning_ICCV_2023_paper.html)] [[CODE](https://github.com/czhang024/CI-Net)] [[SUPP](https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zhang_Generative_Gradient_Inversion_ICCV_2023_supplemental.pdf)] | @@ -1037,12 +1037,12 @@ Federated Learning papers accepted by top AI and NLP conference and journal, inc |Title | Affiliation | Venue | Year | Materials| | ------------------------------------------------------------ | ------------------------------------------------- | -------------- | ---- | ------------------------------------------------------------ | -|Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization | Auburn University | EMNLP | 2023 | [PUB](https://aclanthology.org/2023.emnlp-main.488/) [PDF](https://arxiv.org/abs/2310.15080) [CODE](https://github.com/llm-eff/FedPepTAO) | -| Federated Meta-Learning for Emotion and Sentiment Aware Multi-modal Complaint Identification | IIT Patna | EMNLP | 2023 | [[PUB](https://aclanthology.org/2023.emnlp-main.999/)] [CODE](https://github.com/appy1608/EMNLP2023-Multimodal-Complaint-Detection) | -|FedID: Federated Interactive Distillation for Large-Scale Pretraining Language Models | YNU | EMNLP | 2023 | [PUB](https://aclanthology.org/2023.emnlp-main.529/) [CODE](https://github.com/maxinge8698/FedID) | -|FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning | KAIST | EMNLP | 2023 | [PUB](https://aclanthology.org/2023.emnlp-main.734/) [PDF](https://arxiv.org/abs/2310.16538) | -|Coordinated Replay Sample Selection for Continual Federated Learning | CMU | EMNLP industry Track | 2023 | [PUB](https://aclanthology.org/2023.emnlp-industry.32/) [PDF](https://arxiv.org/abs/2310.15054) | -|Tunable Soft Prompts are Messengers in Federated Learning | SYSU | EMNLP Findings | 2023 | [PUB](https://aclanthology.org/2023.findings-emnlp.976/) [PDF](https://arxiv.org/abs/2311.06805) [CODE](https://github.com/alibaba/FederatedScope/tree/fedsp/federatedscope/nlp/fedsp) | +| Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization | Auburn University | EMNLP | 2023 | [[PUB](https://aclanthology.org/2023.emnlp-main.488/)] [[PDF](https://arxiv.org/abs/2310.15080)] [[CODE](https://github.com/llm-eff/FedPepTAO)] | +| Federated Meta-Learning for Emotion and Sentiment Aware Multi-modal Complaint Identification | IIT Patna | EMNLP | 2023 | [[PUB](https://aclanthology.org/2023.emnlp-main.999/)] [[CODE](https://github.com/appy1608/EMNLP2023-Multimodal-Complaint-Detection)] | +| FedID: Federated Interactive Distillation for Large-Scale Pretraining Language Models | YNU | EMNLP | 2023 | [[PUB](https://aclanthology.org/2023.emnlp-main.529/)] [[CODE](https://github.com/maxinge8698/FedID)] | +| FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning | KAIST | EMNLP | 2023 | [[PUB](https://aclanthology.org/2023.emnlp-main.734/)] [[PDF](https://arxiv.org/abs/2310.16538)] | +| Coordinated Replay Sample Selection for Continual Federated Learning | CMU | EMNLP industry Track | 2023 | [[PUB](https://aclanthology.org/2023.emnlp-industry.32/)] [[PDF](https://arxiv.org/abs/2310.15054)] | +| Tunable Soft Prompts are Messengers in Federated Learning | SYSU | EMNLP Findings | 2023 | [[PUB](https://aclanthology.org/2023.findings-emnlp.976/)] [[PDF](https://arxiv.org/abs/2311.06805)] [[CODE](https://github.com/alibaba/FederatedScope/tree/fedsp/federatedscope/nlp/fedsp)] | | Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms | OSU | ACL | 2023 | [[PUB](https://aclanthology.org/2023.acl-long.678/)] [[PDF](https://arxiv.org/abs/2305.17221)] [[CODE](https://github.com/osu-nlp-group/fl4semanticparsing)] | | FEDLEGAL: The First Real-World Federated Learning Benchmark for Legal NLP | HIT; Peng Cheng Lab | ACL | 2023 | [[PUB](https://aclanthology.org/2023.acl-long.193/)] [[CODE](https://github.com/SMILELab-FL/FedLegal)] | | Client-Customized Adaptation for Parameter-Efficient Federated Learning | | ACL Findings | 2023 | [[PUB](https://aclanthology.org/2023.findings-acl.75/)] | @@ -1133,11 +1133,11 @@ Federated Learning papers accepted by top Database conference and journal, inclu | Distribution-Regularized Federated Learning on Non-IID Data | BUAA | ICDE | 2023 | [[PUB](https://ieeexplore.ieee.org/document/10184650)] | | Fed-SC: One-Shot Federated Subspace Clustering over High-Dimensional Data | ShanghaiTech University | ICDE | 2023 | [[PUB](https://ieeexplore.ieee.org/document/10184550)] [[CODE](https://github.com/SongjieXie/Fed-SC)] | | FLBooster: A Unified and Efficient Platform for Federated Learning Acceleration | ZJU | ICDE | 2023 | [[PUB](https://ieeexplore.ieee.org/document/10184883)] | -| FedGTA: Topology-aware Averaging for Federated Graph Learning. | BIT | VLDB | 2023 | [PUB](https://www.vldb.org/pvldb/vol17/p41-li.pdf) [CODE](https://github.com/xkLi-Allen/FedGTA) | -| FS-Real: A Real-World Cross-Device Federated Learning Platform. | Alibaba Group | VLDB | 2023 | [PUB](https://www.vldb.org/pvldb/vol16/p4046-chen.pdf) [PDF](https://arxiv.org/abs/2303.13363) [CODE](https://github.com/alibaba/FederatedScope/tree/FSreal) | -| Federated Calibration and Evaluation of Binary Classifiers. | meta | VLDB | 2023 | [PUB](https://www.vldb.org/pvldb/vol16/p3253-cormode.pdf) [PDF](https://arxiv.org/abs/2210.12526) [CODE](https://figshare.com/s/607998e479b0778645f6) | -| Olive: Oblivious Federated Learning on Trusted Execution Environment Against the Risk of Sparsification. | Kyoto University | VLDB | 2023 | [PUB](https://www.vldb.org/pvldb/vol16/p2404-kato.pdf) [PDF](https://arxiv.org/abs/2202.07165) [CODE](https://github.com/FumiyukiKato/FL-TEE) | -| Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System. | NUS | VLDB | 2023 | [PUB](https://www.vldb.org/pvldb/vol16/p2471-ooi.pdf) [CODE](https://github.com/nusdbsystem/falcon) | +| FedGTA: Topology-aware Averaging for Federated Graph Learning. | BIT | VLDB | 2023 | [[PUB](https://www.vldb.org/pvldb/vol17/p41-li.pdf)] [[CODE](https://github.com/xkLi-Allen/FedGTA)] | +| FS-Real: A Real-World Cross-Device Federated Learning Platform. | Alibaba Group | VLDB | 2023 | [[PUB](https://www.vldb.org/pvldb/vol16/p4046-chen.pdf)] [[PDF](https://arxiv.org/abs/2303.13363)] [[CODE](https://github.com/alibaba/FederatedScope/tree/FSreal)] | +| Federated Calibration and Evaluation of Binary Classifiers. | meta | VLDB | 2023 | [[PUB](https://www.vldb.org/pvldb/vol16/p3253-cormode.pdf)] [[PDF](https://arxiv.org/abs/2210.12526)] [[CODE](https://figshare.com/s/607998e479b0778645f6)] | +| Olive: Oblivious Federated Learning on Trusted Execution Environment Against the Risk of Sparsification. | Kyoto University | VLDB | 2023 | [[PUB](https://www.vldb.org/pvldb/vol16/p2404-kato.pdf)] [[PDF](https://arxiv.org/abs/2202.07165)] [[CODE](https://github.com/FumiyukiKato/FL-TEE)] | +| Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System. | NUS | VLDB | 2023 | [[PUB](https://www.vldb.org/pvldb/vol16/p2471-ooi.pdf)] [[CODE](https://github.com/nusdbsystem/falcon)] | | Differentially Private Vertical Federated Clustering. | Purdue University | VLDB | 2023 | [[PUB](https://www.vldb.org/pvldb/vol16/p1277-li.pdf)] [[PDF](https://arxiv.org/abs/2208.01700)] [[CODE](https://anonymous.4open.science/r/public_vflclustering-63CD/README.md)] | | FederatedScope: A Flexible Federated Learning Platform for Heterogeneity. :fire: | Alibaba | VLDB | 2023 | [[PUB](https://www.vldb.org/pvldb/vol16/p1059-li.pdf)] [[PDF](https://arxiv.org/abs/2204.05011)] [[CODE](https://github.com/alibaba/FederatedScope)] | | Secure Shapley Value for Cross-Silo Federated Learning. | Kyoto University | VLDB | 2023 | [[PUB](https://www.vldb.org/pvldb/vol16/p1657-zheng.pdf)] [[PDF](https://arxiv.org/abs/2209.04856)] [[CODE](https://github.com/teijyogen/secsv)] | @@ -1326,7 +1326,7 @@ Federated Learning papers accepted by top Database conference and journal, inclu | FLINT: A Platform for Federated Learning Integration | LinkedIn | MLSys | 2023 | [[PUB](https://proceedings.mlsys.org/paper_files/paper/2023/hash/d3313de3f431fd64513431c4326d237c-Abstract-mlsys2023.html)] [[PDF](https://arxiv.org/abs/2302.12862)] | | On Noisy Evaluation in Federated Hyperparameter Tuning | CMU | MLSys | 2023 | [[PUB](https://proceedings.mlsys.org/paper_files/paper/2023/hash/294f82c43d69f66c04440cbb2740e52d-Abstract-mlsys2023.html)] [[PDF](https://arxiv.org/abs/2212.08930)] [[CODE](https://github.com/imkevinkuo/noisy-eval-in-fl)] | | GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning | UBC | MLSys | 2023 | [[PUB](https://proceedings.mlsys.org/paper_files/paper/2023/hash/3ed923f9f88108cb066c6568d3df2666-Abstract-mlsys2023.html)] [[PDF](https://arxiv.org/abs/2212.01523)] [[CODE](https://github.com/TCtower/GlueFL)] | -| Self-Supervised On-Device Federated Learning From Unlabeled Streams. | FDU | TCAD | 2023 | [[PUB](https://ieeexplore.ieee.org/document/10128673)] [PDF](https://arxiv.org/abs/2212.01006) | +| Self-Supervised On-Device Federated Learning From Unlabeled Streams. | FDU | TCAD | 2023 | [[PUB](https://ieeexplore.ieee.org/document/10128673)] [[PDF](https://arxiv.org/abs/2212.01006)] | | Optimizing Training Efficiency and Cost of Hierarchical Federated Learning in Heterogeneous Mobile-Edge Cloud Computing | ECNU | TCAD | 2023 | [[PUB](https://ieeexplore.ieee.org/document/9882092)] | | Lightweight Blockchain-Empowered Secure and Efficient Federated Edge Learning | University of Exeter | TC | 2023 | [[PUB](https://ieeexplore.ieee.org/document/10177803)] | | Towards Data-Independent Knowledge Transfer in Model-Heterogeneous Federated Learning | PolyU | TC | 2023 | [[PUB](https://ieeexplore.ieee.org/document/10115052)] | diff --git a/data.yaml b/data.yaml index 9ab5d5f..c074b78 100644 --- a/data.yaml +++ b/data.yaml @@ -3542,6 +3542,20 @@ fl-in-top-ml-conference-and-journal: PUB: https://jmlr.org/papers/v24/22-0689.html PDF: https://arxiv.org/abs/2206.10189 CODE: https://github.com/Accenture/Labs-Federated-Learning/tree/asynchronous_FL + - title: Tighter Regret Analysis and Optimization of Online Federated Learning + affiliation: Hanyang University + venue: TPAMI + year: '2023' + materials: + PUB: https://ieeexplore.ieee.org/document/10255290 + PDF: https://arxiv.org/abs/2205.06491 + - title: Efficient Federated Learning Via Local Adaptive Amended Optimizer With + Linear Speedup + affiliation: University of Sydney + venue: TPAMI + year: '2023' + materials: + PDF: https://arxiv.org/abs/2308.00522 - title: Federated Learning Via Inexact ADMM. affiliation: BJTU venue: TPAMI @@ -6320,6 +6334,51 @@ fl-in-top-secure-conference-and-journal: year: 4 materials: 60 body: + - title: Turning Privacy-preserving Mechanisms against Federated Learning + affiliation: University of Pavia + venue: CCS + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3576915.3623114 + PDF: https://arxiv.org/abs/2305.05355 + - title: 'MESAS: Poisoning Defense for Federated Learning Resilient against Adaptive + Attackers' + affiliation: University of Würzburg + venue: CCS + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3576915.3623212 + - title: 'martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable + Federated Learning Architecture' + affiliation: THU + venue: CCS + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3576915.3623134 + PDF: https://arxiv.org/abs/2309.01098 + CODE: https://github.com/liqi16/martfl + - title: Unraveling the Connections between Privacy and Certified Robustness in + Federated Learning Against Poisoning Attacks + affiliation: UIUC + venue: CCS + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3576915.3623193 + PDF: https://arxiv.org/abs/2209.04030 + - title: 'Poster: Verifiable Data Valuation with Strong Fairness in Horizontal Federated + Learning' + affiliation: NSYSU + venue: CCS + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3576915.3624371 + - title: 'Poster: Bridging Trust Gaps: Data Usage Transparency in Federated Data + Ecosystems' + affiliation: RWTH Aachen University + venue: CCS + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3576915.3624371 - title: 'Every Vote Counts: Ranking-Based Training of Federated Learning to Resist Poisoning Attacks' affiliation: University of Massachusetts Amherst @@ -6652,6 +6711,126 @@ fl-in-top-cv-conference-and-journal: year: 4 materials: 60 body: + - title: 'FedCE: Personalized Federated Learning Method based on Clustering Ensembles' + affiliation: BJTU + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3612217 + - title: 'FedVQA: Personalized Federated Visual Question Answering over Heterogeneous + Scenes' + affiliation: Leiden University + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3611958 + - title: 'Towards Fast and Stable Federated Learning: Confronting Heterogeneity + via Knowledge Anchor' + affiliation: XJTU + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3612597 + PDF: https://arxiv.org/abs/2312.02416 + CODE: https://github.com/J1nqianChen/FedKA + - title: Federated Deep Multi-View Clustering with Global Self-Supervision + affiliation: UESTC + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3612027 + PDF: https://arxiv.org/abs/2309.13697 + - title: 'FedAA: Using Non-sensitive Modalities to Improve Federated Learning while + Preserving Image Privacy' + affiliation: ZJU + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3611953 + - title: Prototype-guided Knowledge Transfer for Federated Unsupervised Cross-modal + Hashing + affiliation: SDNU + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3613837 + CODE: https://github.com/exquisite1210/PT-FUCH_P + - title: Joint Local Relational Augmentation and Global Nash Equilibrium for Federated + Learning with Non-IID Data + affiliation: ZJU + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3612178 + PDF: https://arxiv.org/abs/2308.11646 + - title: 'FedCD: A Classifier Debiased Federated Learning Framework for Non-IID + Data' + affiliation: BUPT + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3611966 + - title: Federated Learning with Label-Masking Distillation + affiliation: UCAS + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3611984 + CODE: https://github.com/wnma3mz/FedLMD + - title: Cross-Silo Prototypical Calibration for Federated Learning with Non-IID + Data + affiliation: SDU + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3612481 + PDF: https://arxiv.org/abs/2308.03457 + CODE: https://github.com/qizhuang-qz/FedCSPC + - title: A Four-Pronged Defense Against Byzantine Attacks in Federated Learning + affiliation: HUST + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3612474 + PDF: https://arxiv.org/abs/2308.03331 + - title: Client-Adaptive Cross-Model Reconstruction Network for Modality-Incomplete + Multimodal Federated Learning + affiliation: CAS; Peng Cheng Laboratory; UCAS + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3611757 + - title: 'FedGH: Heterogeneous Federated Learning with Generalized Global Header' + affiliation: NKU + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3611781 + PDF: https://arxiv.org/abs/2303.13137 + CODE: https://github.com/LipingYi/FedGH + - title: 'Cuing Without Sharing: A Federated Cued Speech Recognition Framework via + Mutual Knowledge Distillation' + affiliation: CUHK + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3612134 + PDF: https://arxiv.org/abs/2308.03432 + CODE: https://github.com/yuxuanzhang0713/fedcsr + - title: 'AffectFAL: Federated Active Affective Computing with Non-IID Data' + affiliation: TJUT + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3612442 + CODE: https://github.com/AffectFAL/AffectFAL + - title: Improving Federated Person Re-Identification through Feature-Aware Proximity + and Aggregation + affiliation: SZU + venue: MM + year: '2023' + materials: + PUB: https://dl.acm.org/doi/10.1145/3581783.3612350 - title: Towards Attack-tolerant Federated Learning via Critical Parameter Analysis affiliation: KAIST venue: ICCV @@ -7545,6 +7724,54 @@ fl-in-top-nlp-conference-and-journal: year: 4 materials: 60 body: + - title: Federated Learning of Large Language Models with Parameter-Efficient Prompt + Tuning and Adaptive Optimization + affiliation: Auburn University + venue: EMNLP + year: '2023' + materials: + PUB: https://aclanthology.org/2023.emnlp-main.488/ + PDF: https://arxiv.org/abs/2310.15080 + CODE: https://github.com/llm-eff/FedPepTAO + - title: Federated Meta-Learning for Emotion and Sentiment Aware Multi-modal Complaint + Identification + affiliation: IIT Patna + venue: EMNLP + year: '2023' + materials: + PUB: https://aclanthology.org/2023.emnlp-main.999/ + CODE: https://github.com/appy1608/EMNLP2023-Multimodal-Complaint-Detection + - title: 'FedID: Federated Interactive Distillation for Large-Scale Pretraining + Language Models' + affiliation: YNU + venue: EMNLP + year: '2023' + materials: + PUB: https://aclanthology.org/2023.emnlp-main.529/ + CODE: https://github.com/maxinge8698/FedID + - title: 'FedTherapist: Mental Health Monitoring with User-Generated Linguistic + Expressions on Smartphones via Federated Learning' + affiliation: KAIST + venue: EMNLP + year: '2023' + materials: + PUB: https://aclanthology.org/2023.emnlp-main.734/ + PDF: https://arxiv.org/abs/2310.16538 + - title: Coordinated Replay Sample Selection for Continual Federated Learning + affiliation: CMU + venue: EMNLP industry Track + year: '2023' + materials: + PUB: https://aclanthology.org/2023.emnlp-industry.32/ + PDF: https://arxiv.org/abs/2310.15054 + - title: Tunable Soft Prompts are Messengers in Federated Learning + affiliation: SYSU + venue: EMNLP Findings + year: '2023' + materials: + PUB: https://aclanthology.org/2023.findings-emnlp.976/ + PDF: https://arxiv.org/abs/2311.06805 + CODE: https://github.com/alibaba/FederatedScope/tree/fedsp/federatedscope/nlp/fedsp - title: 'Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms' affiliation: OSU @@ -7598,32 +7825,6 @@ fl-in-top-nlp-conference-and-journal: materials: PUB: https://aclanthology.org/2023.acl-industry.60/ PDF: https://arxiv.org/abs/2305.18465 - - title: 'Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise - Krum-Based Aggregation' - affiliation: PKU - venue: EMNLP - year: '2022' - materials: - PUB: https://aclanthology.org/2022.findings-emnlp.25/ - PDF: https://arxiv.org/abs/2210.06894 - - title: Efficient Federated Learning on Knowledge Graphs via Privacy-preserving - Relation Embedding Aggregation **`kg.`** - affiliation: Lehigh University - venue: EMNLP - year: '2022' - materials: - PUB: https://aclanthology.org/2022.findings-emnlp.43/ - PDF: https://arxiv.org/abs/2203.09553 - CODE: https://github.com/taokz/FedR - - title: Federated Continual Learning for Text Classification via Selective Inter-client - Transfer - affiliation: DRIMCo GmbH; LMU - venue: EMNLP - year: '2022' - materials: - PUB: https://aclanthology.org/2022.findings-emnlp.353 - PDF: https://arxiv.org/abs/2210.06101 - CODE: https://github.com/raipranav/fcl-fedseit - title: Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient Ensembling affiliation: SNU @@ -7647,21 +7848,40 @@ fl-in-top-nlp-conference-and-journal: materials: PUB: https://aclanthology.org/2022.emnlp-main.430 CODE: https://github.com/SMILELab-FL/FedVocab - - title: Federated Meta-Learning for Emotion and Sentiment Aware Multi-modal Complaint - Identification - affiliation: '' - venue: EMNLP - year: '2022' - materials: - PUB: https://openreview.net/forum?id=rVgVJ9eWxM9 - title: Fair NLP Models with Differentially Private Text Encoders - affiliation: '' + affiliation: Univ. Lille venue: EMNLP year: '2022' materials: - PUB: https://openreview.net/forum?id=BVgNSki6q1c + PUB: https://aclanthology.org/2022.findings-emnlp.514/ PDF: https://arxiv.org/abs/2205.06135 CODE: https://github.com/saist1993/dpnlp + - title: Federated Continual Learning for Text Classification via Selective Inter-client + Transfer + affiliation: DRIMCo GmbH; LMU + venue: EMNLP Findings + year: '2022' + materials: + PUB: https://aclanthology.org/2022.findings-emnlp.353 + PDF: https://arxiv.org/abs/2210.06101 + CODE: https://github.com/raipranav/fcl-fedseit + - title: Efficient Federated Learning on Knowledge Graphs via Privacy-preserving + Relation Embedding Aggregation **`kg.`** + affiliation: Lehigh University + venue: EMNLP Findings + year: '2022' + materials: + PUB: https://aclanthology.org/2022.findings-emnlp.43/ + PDF: https://arxiv.org/abs/2203.09553 + CODE: https://github.com/taokz/FedR + - title: 'Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise + Krum-Based Aggregation' + affiliation: PKU + venue: EMNLP Findings + year: '2022' + materials: + PUB: https://aclanthology.org/2022.findings-emnlp.25/ + PDF: https://arxiv.org/abs/2210.06894 - title: Scaling Language Model Size in Cross-Device Federated Learning affiliation: Google venue: ACL workshop @@ -7715,14 +7935,6 @@ fl-in-top-nlp-conference-and-journal: PUB: https://aclanthology.org/2022.naacl-main.101 PDF: https://arxiv.org/abs/2206.02291 CODE: https://github.com/orionw/multilingual-federated-learning - - title: Training Mixed-Domain Translation Models via Federated Learning - affiliation: Amazon - venue: NAACL - year: '2022' - materials: - PUB: https://aclanthology.org/2022.naacl-main.186/ - PAGE: https://www.amazon.science/publications/training-mixed-domain-translation-models-via-federated-learning - PDF: https://arxiv.org/abs/2205.01557 - title: Federated Chinese Word Segmentation with Global Character Associations affiliation: University of Washington venue: ACL workshop @@ -7888,6 +8100,46 @@ fl-in-top-db-conference-and-journal: year: '2023' materials: PUB: https://ieeexplore.ieee.org/document/10184883 + - title: 'FedGTA: Topology-aware Averaging for Federated Graph Learning.' + affiliation: BIT + venue: VLDB + year: '2023' + materials: + PUB: https://www.vldb.org/pvldb/vol17/p41-li.pdf + CODE: https://github.com/xkLi-Allen/FedGTA + - title: 'FS-Real: A Real-World Cross-Device Federated Learning Platform.' + affiliation: Alibaba Group + venue: VLDB + year: '2023' + materials: + PUB: https://www.vldb.org/pvldb/vol16/p4046-chen.pdf + PDF: https://arxiv.org/abs/2303.13363 + CODE: https://github.com/alibaba/FederatedScope/tree/FSreal + - title: Federated Calibration and Evaluation of Binary Classifiers. + affiliation: meta + venue: VLDB + year: '2023' + materials: + PUB: https://www.vldb.org/pvldb/vol16/p3253-cormode.pdf + PDF: https://arxiv.org/abs/2210.12526 + CODE: https://figshare.com/s/607998e479b0778645f6 + - title: 'Olive: Oblivious Federated Learning on Trusted Execution Environment Against + the Risk of Sparsification.' + affiliation: Kyoto University + venue: VLDB + year: '2023' + materials: + PUB: https://www.vldb.org/pvldb/vol16/p2404-kato.pdf + PDF: https://arxiv.org/abs/2202.07165 + CODE: https://github.com/FumiyukiKato/FL-TEE + - title: 'Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning + System.' + affiliation: NUS + venue: VLDB + year: '2023' + materials: + PUB: https://www.vldb.org/pvldb/vol16/p2471-ooi.pdf + CODE: https://github.com/nusdbsystem/falcon - title: Differentially Private Vertical Federated Clustering. affiliation: Purdue University venue: VLDB @@ -8939,6 +9191,13 @@ fl-in-top-system-conference-and-journal: PUB: https://proceedings.mlsys.org/paper_files/paper/2023/hash/3ed923f9f88108cb066c6568d3df2666-Abstract-mlsys2023.html PDF: https://arxiv.org/abs/2212.01523 CODE: https://github.com/TCtower/GlueFL + - title: Self-Supervised On-Device Federated Learning From Unlabeled Streams. + affiliation: FDU + venue: TCAD + year: '2023' + materials: + PUB: https://ieeexplore.ieee.org/document/10128673 + PDF: https://arxiv.org/abs/2212.01006 - title: Optimizing Training Efficiency and Cost of Hierarchical Federated Learning in Heterogeneous Mobile-Edge Cloud Computing affiliation: ECNU @@ -8946,6 +9205,12 @@ fl-in-top-system-conference-and-journal: year: '2023' materials: PUB: https://ieeexplore.ieee.org/document/9882092 + - title: Lightweight Blockchain-Empowered Secure and Efficient Federated Edge Learning + affiliation: University of Exeter + venue: TC + year: '2023' + materials: + PUB: https://ieeexplore.ieee.org/document/10177803 - title: Towards Data-Independent Knowledge Transfer in Model-Heterogeneous Federated Learning affiliation: PolyU @@ -9002,6 +9267,13 @@ fl-in-top-system-conference-and-journal: year: '2023' materials: PUB: https://ieeexplore.ieee.org/document/9791849/ + - title: 'CHEESE: Distributed Clustering-Based Hybrid Federated Split Learning Over + Edge Networks' + affiliation: SUDA + venue: TPDS + year: '2023' + materials: + PUB: https://ieeexplore.ieee.org/document/10274134 - title: Hierarchical Federated Learning With Momentum Acceleration in Multi-Tier Networks affiliation: University of Sydney