Copertina

On the Asymptotics of Self-Supervised Pre-training: Two-Stage M-Estimation and Representation Symmetry

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Tinati, Mohammad, Tu, Stephen
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Stability properties of gradient flow dynamics for the symmetric low-rank matrix factorization problem
di: Mohammadi, Hesameddin, et al.
Pubblicazione: (2024)

DeCoP: Enhancing Self-Supervised Time Series Representation with Dependency Controlled Pre-training
di: Wu, Yuemin, et al.
Pubblicazione: (2025)

The Impact of Semantic Pairs on Self-Supervised Representation Learning
di: Alkhalefi, Mohammad, et al.
Pubblicazione: (2025)

SuPreME: A Supervised Pre-training Framework for Multimodal ECG Representation Learning
di: Cai, Mingsheng, et al.
Pubblicazione: (2025)

A Self-Supervised Paradigm for Data-Efficient Medical Foundation Model Pre-training: V-information Optimization Framework
di: Yang, Wenxuan, et al.
Pubblicazione: (2024)

Adaptive Kernel Density Estimation with Pre-training
di: Zhang, Ruitong, et al.
Pubblicazione: (2026)

Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training
di: Dave, Vedant, et al.
Pubblicazione: (2024)

Multi-instance Learning as Downstream Task of Self-Supervised Learning-based Pre-trained Model
di: Matsuishi, Koki, et al.
Pubblicazione: (2025)

Self-Supervised Learning for Pre-training Capsule Networks: Overcoming Medical Imaging Dataset Challenges
di: El-Shimy, Heba, et al.
Pubblicazione: (2025)

Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization
di: Chakraborty, Deep, et al.
Pubblicazione: (2024)

Self-Supervised Radio Pre-training: Toward Foundational Models for Spectrogram Learning
di: Aboulfotouh, Ahmed, et al.
Pubblicazione: (2024)

Quantifying the Pre-training Dividend: Generative versus Latent Self-Supervised Learning for Time Series Foundation Models
di: Major, Noam, et al.
Pubblicazione: (2026)

Self-Supervised Contrastive Pre-Training for Multivariate Point Processes
di: Shou, Xiao, et al.
Pubblicazione: (2024)

Label-Efficient Sleep Staging Using Transformers Pre-trained with Position Prediction
di: Lala, Sayeri, et al.
Pubblicazione: (2024)

Domain-Adaptive Pre-training of Self-Supervised Foundation Models for Medical Image Classification in Gastrointestinal Endoscopy
di: Roth, Marcel, et al.
Pubblicazione: (2024)

Cross-Domain Pre-training with Language Models for Transferable Time Series Representations
di: Cheng, Mingyue, et al.
Pubblicazione: (2024)

Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-training
di: Guo, Quanjiang, et al.
Pubblicazione: (2025)

Gaussian Joint Embeddings For Self-Supervised Representation Learning
di: Huang, Yongchao
Pubblicazione: (2026)

Gaussian Joint Embeddings For Self-Supervised Representation Learning
di: Huang, Yongchao
Pubblicazione: (2026)

Self-Supervised Representation Learning as Mutual Information Maximization
di: Sabby, Akhlaqur Rahman, et al.
Pubblicazione: (2025)

On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning
di: Wang, Bokun, et al.
Pubblicazione: (2024)

Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
di: Mialon, Grégoire, et al.
Pubblicazione: (2023)

Self-Supervised Pre-Training for Precipitation Post-Processor
di: An, Sojung, et al.
Pubblicazione: (2023)

Contrastive-to-Self-Supervised: A Two-Stage Framework for Script Similarity Learning
di: Roman, Claire, et al.
Pubblicazione: (2026)

Self-Supervised Learning for Covariance Estimation
di: Diskin, Tzvi, et al.
Pubblicazione: (2024)

Self-Supervised Dynamical System Representations for Physiological Time-Series
di: Chen, Yenho, et al.
Pubblicazione: (2025)

HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
di: Kim, Sunwoo, et al.
Pubblicazione: (2024)

Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints
di: Cui, Xiaodong, et al.
Pubblicazione: (2025)

Pre-training LLM without Learning Rate Decay Enhances Supervised Fine-Tuning
di: Yano, Kazuki, et al.
Pubblicazione: (2026)

Pre-trained Tabular Foundation Models as Versatile Summary Networks for Neural Posterior Estimation
di: Pickens, Elliot, et al.
Pubblicazione: (2026)

Pre-training Vision Transformers with Formula-driven Supervised Learning
di: Kataoka, Hirokatsu, et al.
Pubblicazione: (2022)

Pre-trained Visual Dynamics Representations for Efficient Policy Learning
di: Luo, Hao, et al.
Pubblicazione: (2024)

Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift
di: Zhang, Zhen, et al.
Pubblicazione: (2025)

Two Approaches to Direct Estimation of Riesz Representers
di: Bruns-Smith, David
Pubblicazione: (2026)

Self-Supervised Detection of Perfect and Partial Input-Dependent Symmetries
di: Urbano, Alonso, et al.
Pubblicazione: (2023)

COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning
di: Meng, Chuizheng, et al.
Pubblicazione: (2023)

AdaMR: Adaptable Molecular Representation for Unified Pre-training Strategy
di: Ding, Yan, et al.
Pubblicazione: (2023)

Self-Supervised Graph Representation Learning via Global Context Prediction
di: Peng, Zhen, et al.
Pubblicazione: (2020)

Learning Representation for Multitask learning through Self Supervised Auxiliary learning
di: Shin, Seokwon, et al.
Pubblicazione: (2024)

Adv-SSL: Adversarial Self-Supervised Representation Learning with Theoretical Guarantees
di: Duan, Chenguang, et al.
Pubblicazione: (2024)