Image de couverture de livre

LF2L: Loss Fusion Horizontal Federated Learning Across Heterogeneous Feature Spaces Using External Datasets Effectively: A Case Study in Second Primary Cancer Prediction

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lin, Chia-Fu, Tseng, Yi-Ju
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Federated Learning for Epileptic Seizure Prediction Across Heterogeneous EEG Datasets
par: Baykara, Cem Ata, et autres
Publié: (2025)

An Effective UNet Using Feature Interaction and Fusion for Organ Segmentation in Medical Image
par: Gou, Xiaolin, et autres
Publié: (2024)

Federated Imputation under Heterogeneous Feature Spaces
par: Hocine, Imane, et autres
Publié: (2026)

L-ReLF: A Framework for Lexical Dataset Creation
par: Sedrati, Anass, et autres
Publié: (2026)

Loss on ignition of sediment core LF3
par: Lenz, Conny, et autres
Publié: (2015)

Federated Causal Discovery Across Heterogeneous Datasets under Latent Confounding
par: Hahn, Maximilian, et autres
Publié: (2026)

FedLF: Adaptive Logit Adjustment and Feature Optimization in Federated Long-Tailed Learning
par: Lu, Xiuhua, et autres
Publié: (2024)

Effectiveness of Predicting Event‐Level Interception Losses Across Diverse Vegetated Sites Using Statistical Models
par: Abigail G. Sandquist, et autres
Publié: (2025)

Frequency-aware Feature Fusion for Dense Image Prediction
par: Chen, Linwei, et autres
Publié: (2024)

Quantum State Evolution and Berry Potentials at Exceptional Points and Quantum Phase Transitions
par: Ju, Chia-Yi, et autres
Publié: (2024)

Effect of Preoperative Transarterial Embolization on Surgical Blood Loss in Thyroidectomy for Large Graves' Disease
par: Shun‐Yu Chi, et autres
Publié: (2026)

What's the difference? / L.F. Velero
par: Velero, L.F

Transporting Theorems about Typeability in LF Across Schematically Defined Contexts
par: Johnson, Chase, et autres
Publié: (2025)

FLASH: Federated Learning Across Simultaneous Heterogeneities
par: Chang, Xiangyu, et autres
Publié: (2024)

NPCNet: Navigator-Driven Pseudo Text for Deep Clustering of Early Sepsis Phenotyping
par: Tsai, Pi-Ju, et autres
Publié: (2026)

MoLF: Mixture-of-Latent-Flow for Pan-Cancer Spatial Gene Expression Prediction from Histology
par: Hu, Susu, et autres
Publié: (2026)

Radiomic Feature‐Based Prediction of Primary Cancer Origins in Brain Metastases Using Machine Learning
par: Dilek Betül Sarıdede, et autres
Publié: (2025)

The Importance of Molecular Subtyping in Predicting Second Primary Malignancy Risk in Colorectal Cancer
par: Muhammad Hasan, et autres
Publié: (2025)

KAT-GNN: A Knowledge-Augmented Temporal Graph Neural Network for Risk Prediction in Electronic Health Records
par: Lin, Kun-Wei, et autres
Publié: (2025)

Dataset for ASE 2026 paper: Why Fuzzers Differ: Dissecting Strategy Effectiveness Across Heterogeneous Greybox Fuzzers
par: Anonymous
Publié: (2026)

Prostate Cancer Classification Using Multimodal Feature Fusion and Explainable AI
par: Khan, Asma Sadia, et autres
Publié: (2025)

Loss Gap Parity for Fairness in Heterogeneous Federated Learning
par: Erraji, Brahim, et autres
Publié: (2026)

A Rare Case of Disseminated Extrapulmonary Tuberculosis Diagnosed by Endoscopic Ultrasonography‐Guided Fine‐Needle Biopsy: A Case Report
par: Yi‐Lin Lin, et autres
Publié: (2026)

Second primary malignancies in Asian chronic lymphocytic leukaemia patients: A Taiwan Cancer Registry Study
par: Yi‐Wei Lee, et autres
Publié: (2026)

The Heterogeneous Earnings Impact of Job Loss Across Workers, Establishments, and Markets
par: Athey, Susan, et autres
Publié: (2023)

SG-XDEAT: Sparsity-Guided Cross-Dimensional and Cross-Encoding Attention with Target-Aware Conditioning in Tabular Learning
par: Cheng, Chih-Chuan, et autres
Publié: (2025)

MedM2T: A MultiModal Framework for Time-Aware Modeling with Electronic Health Record and Electrocardiogram Data
par: Kuo, Yu-Chen, et autres
Publié: (2025)

Loss-to-Loss Prediction: Scaling Laws for All Datasets
par: Brandfonbrener, David, et autres
Publié: (2024)

MOVE: Effective and Harmless Ownership Verification via Embedded External Features
par: Li, Yiming, et autres
Publié: (2022)

Exploiting Features and Logits in Heterogeneous Federated Learning
par: Chan, Yun-Hin, et autres
Publié: (2022)

The Case for a Horizontal Federated AI operating System for Telcos
par: Barros, Sebastian
Publié: (2025)

Benchmarking Anomaly Detection Across Heterogeneous Cloud Telemetry Datasets
par: Islam, Mohammad Saiful, et autres
Publié: (2026)

Survival Prediction Across Diverse Cancer Types Using Neural Networks
par: Yan, Xu, et autres
Publié: (2024)

Tackling Data Heterogeneity in Federated Learning via Loss Decomposition
par: Zeng, Shuang, et autres
Publié: (2024)

Transfer Learning for Loan Recovery Prediction under Distribution Shifts with Heterogeneous Feature Spaces
par: Gerling, Christopher, et autres
Publié: (2026)

Adaptive Real-Time Multi-Loss Function Optimization Using Dynamic Memory Fusion Framework: A Case Study on Breast Cancer Segmentation
par: Golnari, Amin, et autres
Publié: (2024)

Survival Effectiveness of Uniport Anatomic Resections in Patients With Clinical Stage I Lung Cancer: An Observation Cohort Study
par: Ching Feng Wu, et autres
Publié: (2025)

Multiscale Feature Learning Using Co-Tuplet Loss for Offline Handwritten Signature Verification
par: Huang, Fu-Hsien, et autres
Publié: (2023)

Second Primary Lung Cancer Associated With Family History of Lung Cancer
par: Frantisek Zitricky, et autres
Publié: (2025)

Towards Multi-modality Fusion and Prototype-based Feature Refinement for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound
par: Wu, Hong, et autres
Publié: (2024)