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Korea AI Labs

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Federated Learning · 연구실 27곳 · 논문 69편

다른 주제·대학과 함께 찾기
POSTECH4/15
KU1/23
Yonsei4/37
KAIST12/57
SNU6/84
칸 하나가 연구실 하나예요. 이 주제 논문이 많을수록 밝아요.

관련 연구실

등급은 학회·저널 분류이며 연구실 순위가 아닙니다.

  1. Yonsei머신러닝

    한동준Edge AI Lab

    관련 논문 24편비중 55%연구 분야에 명시
    • 2026Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection IEEE TMC
    • 2026Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs ICML
    • 2026Multi-Tier Split Federated Learning for Multi-Level Personalization IEEE WCNC
  2. KAIST머신러닝

    문재균

    관련 논문 5편비중 25%연구 분야에 명시
    • 2024Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning ICML
    • 2023EvoFed: Leveraging Evolutionary Strategies for Efficient and Privacy-Preserving Federated Learning NeurIPS
    • 2023Federated Split Learning with Joint Personalization-Generalization for Inference-Stage Optimization in Wireless Edge Networks IEEE TMC
  3. SNU컴퓨터 비전

    이경무, 한보형CV Lab

    관련 논문 3편비중 3%연구 분야에 명시
    • 2025FedLPA: Local Prior Alignment for Heterogeneous Federated Generalized Category Discovery NeurIPS
    • 2024Communication-Efficient Federated Learning with Accelerated Client Gradient CVPR
    • 2024Relaxed Contrastive Learning for Federated Learning CVPR
  4. KAIST머신러닝

    윤세영OSI Lab

    관련 논문 7편비중 5%
    • 2025FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning TMLR
    • 2024FedSOL: Stabilized Orthogonal Learning in Federated Learning CVPR
    • 2024FLR: Label-Mixture Regularization for Federated Learning with Noisy Labels TMLR
  5. SNUAI 시스템

    김형신AIoT Lab

    관련 논문 1편비중 3%연구 분야에 명시
    • 2024Effective Heterogeneous Federated Learning via Efficient Hypernetwork-based Weight Generation SenSys
  6. POSTECH머신러닝

    김동우, 옥정슬, 박상돈, 박은혁ML Lab

    관련 논문 2편비중 2%
    • 2026Federated Variational Preference Alignment with Gumbel-Softmax Prior for Personalized User Preferences ICML
    • 2025Towards Robust and Efficient Federated Low-Rank Adaptation with Heterogeneous Clients ACL
  7. SNU컴퓨터 비전

    김건희Vision & Learning Lab

    관련 논문 3편비중 5%
    • 2025FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields ICCV
    • 2024FedAvP: Augment Local Data via Shared Policy in Federated Learning NeurIPS
    • 2023Federated Learning via Meta-Variational Dropout NeurIPS
  8. POSTECH머신러닝

    이재호EffL Lab

    관련 논문 2편비중 5%
    • 2025Communication-Efficient Split Learning via Adaptive Feature-wise Compression IEEE TNNLS
    • 2025Towards Federated Low-Rank Adaptation with Rank-Heterogeneous Communication NAACL
  9. KAISTAI for Science

    최윤재

    관련 논문 2편비중 3%
    • 2026Federated Learning for Heterogeneous Electronic Health Record Systems with Cost Effective Participant Selection Scientific Reports
    • 2023Towards the Practical Utility of Federated Learning in the Medical Domain CHIL
  10. KAIST머신러닝

    양은호MLI Lab

    관련 논문 2편비중 3%
    • 2025VQ-FedDiff: Federated Learning Algorithm of Diffusion Models with Client-Specific Vector-Quantized Conditioning TPAMI
    • 2023Towards the Practical Utility of Federated Learning in the Medical Domain CHIL
  11. KAIST머신러닝

    황성주MLAI Lab

    관련 논문 2편비중 2%
    • 2025FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA NeurIPS
    • 2023Personalized Subgraph Federated Learning ICML
  12. SNU머신러닝

    김태섭LAAL Lab

    관련 논문 1편비중 3%
    • 2026Generalized and Personalized Federated Learning with Black-Box Foundation Models via Orthogonal Transformations CVPR
  13. SNU자연어처리·LLM

    도재영AIDAS Lab

    관련 논문 1편비중 3%
    • 2026SUM: Unified Geometric Surgery on Spatio-Temporal Adaptation Vectors for Federated Class Incremental Learning ECCV
  14. SNU머신러닝

    이정우CML Lab

    관련 논문 1편비중 2%
    • 2026Federated Offline Reinforcement Learning with Heterogeneous Client Capacities via Progressive Distillation Neurocomputing
  15. KAISTAI 시스템

    김주영CAST Lab

    관련 논문 1편비중 1%
    • 2026NetFED: Network-Aware Acceleration for Multi-Key Privacy-Preserving Federated Learning Aggregation MICRO
  16. Yonsei머신러닝

    손지용ITML Lab

    관련 논문 1편비중 4%
    • 2025Buffer-based Gradient Projection for Continual Federated Learning TMLR
  17. POSTECH음성·오디오

    서영주AIoT Lab

    관련 논문 1편비중 3%
    • 2025HyFLM: A Hypernetwork-Based Federated Learning with Multidimensional Trajectory Optimization on Diffusion Paths Electronics
  18. KAIST데이터 마이닝

    박찬영DSAIL

    관련 논문 1편비중 1%
    • 2025Subgraph Federated Learning for Local Generalization ICLR
  19. KAIST머신러닝

    신진우ALIN Lab

    관련 논문 1편비중 1%
    • 2025NeFL: Nested Model Scaling for Federated Learning with System Heterogeneous Clients IEEE TMC
  20. KAIST머신러닝

    이주호SIML Lab

    관련 논문 1편비중 1%
    • 2025FedSVD: adaptive orthogonalization for private federated learning with LoRA NeurIPS
  21. Yonsei머신러닝

    조성배SCLAB

    관련 논문 1편비중 1%
    • 2025A federated learning approach for classifying chest diseases from chest X-ray images Biomedical Signal Processing and Control
  22. YonseiAI 시스템

    차호정MOBED

    관련 논문 1편비중 5%
    • 2024Split Learning-based Sound Event Detection in Energy-Constrained Sensor Devices IPSN
  23. KAIST컴퓨터 비전

    김승룡CV Lab

    관련 논문 1편비중 1%
    • 2024HeteroSwitch: Characterizing and Taming System-Induced Data Heterogeneity in Federated Learning MLSys
  24. KAIST컴퓨터 비전

    오태현AMI Lab

    관련 논문 1편비중 1%
    • 2024Overcoming Client Data Deficiency in Federated Learning by Exploiting Unlabeled Data on the Server IEEE Access
  25. POSTECH머신러닝

    이남훈Computational Optimization Lab

    관련 논문 1편비중 4%
    • 2023FedFwd: Federated Learning without Backpropagation ICML
  26. KU자연어처리·LLM

    이상근Data Intelligence Lab

    관련 논문 1편비중 3%
    • 2023Client-Customized Adaptation for Parameter-Efficient Federated Learning ACL Findings
  27. KAIST컴퓨터 비전

    주재걸DAVIAN Lab

    관련 논문 1편비중 1%
    • 2023FedGeo: Privacy-Preserving User Next Location Prediction with Federated Learning SIGSPATIAL