Imagen de Portada

A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Gui, Jie, Chen, Tuo, Zhang, Jing, Cao, Qiong, Sun, Zhenan, Luo, Hao, Tao, Dacheng
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trends
por: Younesi, Abolfazl, et al.
Publicado: (2024)

A Survey on Incomplete Multi-label Learning: Recent Advances and Future Trends
por: Li, Xiang, et al.
Publicado: (2024)

Mobility-Aware Federated Self-supervised Learning in Vehicular Network
por: Gu, Xueying, et al.
Publicado: (2024)

Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization
por: Shen, Li, et al.
Publicado: (2026)

SOHES: Self-supervised Open-world Hierarchical Entity Segmentation
por: Cao, Shengcao, et al.
Publicado: (2024)

A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
por: Sun, Yan, et al.
Publicado: (2024)

Incremental Self-training for Semi-supervised Learning
por: Guo, Jifeng, et al.
Publicado: (2024)

A Theoretical Survey on Foundation Models
por: Fu, Shi, et al.
Publicado: (2024)

On the Evolution of Federated Post-Training Large Language Models: A Model Accessibility View
por: Guo, Tao, et al.
Publicado: (2025)

Self-supervised Representation Learning on Electronic Health Records with Graph Kernel Infomax
por: Yao, Hao-Ren, et al.
Publicado: (2022)

Topology-aware Embedding Memory for Continual Learning on Expanding Networks
por: Zhang, Xikun, et al.
Publicado: (2024)

Towards Understanding Generalization and Stability Gaps between Centralized and Decentralized Federated Learning
por: Sun, Yan, et al.
Publicado: (2023)

Convergent Differential Privacy Analysis for General Federated Learning
por: Sun, Yan, et al.
Publicado: (2024)

Federated Distillation: A Survey
por: Li, Lin, et al.
Publicado: (2024)

Continual Learning on Graphs: Challenges, Solutions, and Opportunities
por: Zhang, Xikun, et al.
Publicado: (2024)

Hypergraph Self-supervised Learning with Sampling-efficient Signals
por: Li, Fan, et al.
Publicado: (2024)

On Improving the Algorithm-, Model-, and Data- Efficiency of Self-Supervised Learning
por: Cao, Yun-Hao, et al.
Publicado: (2024)

Automatic Self-supervised Learning for Social Recommendations
por: He, Xin, et al.
Publicado: (2024)

LLM-PS: Empowering Large Language Models for Time Series Forecasting with Temporal Patterns and Semantics
por: Tang, Jialiang, et al.
Publicado: (2025)

Learning Multi-Agent Communication from Graph Modeling Perspective
por: Hu, Shengchao, et al.
Publicado: (2024)

MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs
por: Sun, Yan, et al.
Publicado: (2025)

CktGNN: Circuit Graph Neural Network for Electronic Design Automation
por: Dong, Zehao, et al.
Publicado: (2023)

Pruning Self-attentions into Convolutional Layers in Single Path
por: He, Haoyu, et al.
Publicado: (2021)

Dual-Phase LLM Reasoning: Self-Evolved Mathematical Frameworks
por: Liu, ShaoZhen, et al.
Publicado: (2026)

Mitigating Barren Plateaus in Quantum Denoising Diffusion Probabilistic Model
por: Cao, Haipeng, et al.
Publicado: (2025)

Graph Positional Autoencoders as Self-supervised Learners
por: Liu, Yang, et al.
Publicado: (2025)

Semi-supervised Domain Adaptation in Graph Transfer Learning
por: Qiao, Ziyue, et al.
Publicado: (2023)

Efficient Deep Learning Infrastructures for Embedded Computing Systems: A Comprehensive Survey and Future Envision
por: Luo, Xiangzhong, et al.
Publicado: (2024)

Continual Task Learning through Adaptive Policy Self-Composition
por: Hu, Shengchao, et al.
Publicado: (2024)

A Comprehensive Survey on Joint Resource Allocation Strategies in Federated Edge Learning
por: Zhang, Jingbo, et al.
Publicado: (2024)

Three-Stage Learning Unlocks Strong Performance in Simple Models for Long-Term Time Series Forecasting
por: Yu, Zhenan, et al.
Publicado: (2026)

On Multi-Stage Loss Dynamics in Neural Networks: Mechanisms of Plateau and Descent Stages
por: Chen, Zheng-An, et al.
Publicado: (2024)

Adaptively Point-weighting Curriculum Learning
por: Li, Wensheng, et al.
Publicado: (2025)

Towards Theoretical Understandings of Self-Consuming Generative Models
por: Fu, Shi, et al.
Publicado: (2024)

Diffusion Model-Based Video Editing: A Survey
por: Sun, Wenhao, et al.
Publicado: (2024)

Swarm Learning: A Survey of Concepts, Applications, and Trends
por: Shammar, Elham, et al.
Publicado: (2024)

SpeGCL: Self-supervised Graph Spectrum Contrastive Learning without Positive Samples
por: Shou, Yuntao, et al.
Publicado: (2024)

Exploring the Coordination of Frequency and Attention in Masked Image Modeling
por: Gui, Jie, et al.
Publicado: (2022)

A Survey on Self-supervised Contrastive Learning for Multimodal Text-Image Analysis
por: Khan, Asifullah, et al.
Publicado: (2025)

Partial Feedback Online Learning
por: Shao, Shihao, et al.
Publicado: (2026)