A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
Fuente:
arXiv
Saved in:
| Main Authors: | Lin, Licong, Mei, Song |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Statistical Theory of Contrastive Pre-training and Multimodal Generative AI
by: Oko, Kazusato, et al.
Published: (2025)
by: Oko, Kazusato, et al.
Published: (2025)
Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining
by: Lin, Licong, et al.
Published: (2023)
by: Lin, Licong, et al.
Published: (2023)
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models
by: Suh, Namjoon, et al.
Published: (2024)
by: Suh, Namjoon, et al.
Published: (2024)
Generalized Data Thinning Using Sufficient Statistics
by: Dharamshi, Ameer, et al.
Published: (2023)
by: Dharamshi, Ameer, et al.
Published: (2023)
Statistical Learning Theory for Distributional Classification
by: Fiedler, Christian
Published: (2026)
by: Fiedler, Christian
Published: (2026)
Improved Scaling Laws in Linear Regression via Data Reuse
by: Lin, Licong, et al.
Published: (2025)
by: Lin, Licong, et al.
Published: (2025)
Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
by: Zhou, Leo, et al.
Published: (2024)
by: Zhou, Leo, et al.
Published: (2024)
An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization
by: Chen, Minshuo, et al.
Published: (2024)
by: Chen, Minshuo, et al.
Published: (2024)
Extrapolation in Statistical Learning with Extreme Value Theory
by: Engelke, Sebastian, et al.
Published: (2026)
by: Engelke, Sebastian, et al.
Published: (2026)
Multitask Learning and Bandits via Robust Statistics
by: Xu, Kan, et al.
Published: (2021)
by: Xu, Kan, et al.
Published: (2021)
Statistical Guarantees for Approximate Stationary Points of Shallow Neural Networks
by: Taheri, Mahsa, et al.
Published: (2022)
by: Taheri, Mahsa, et al.
Published: (2022)
Review and Prospect of Algebraic Research in Equivalent Framework between Statistical Mechanics and Machine Learning Theory
by: Watanabe, Sumio
Published: (2024)
by: Watanabe, Sumio
Published: (2024)
Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories
by: Zhang, Haobo, et al.
Published: (2024)
by: Zhang, Haobo, et al.
Published: (2024)
Semi-parametric inference based on adaptively collected data
by: Lin, Licong, et al.
Published: (2023)
by: Lin, Licong, et al.
Published: (2023)
Statistical Decision Theory with Counterfactual Loss
by: Koch, Benedikt, et al.
Published: (2025)
by: Koch, Benedikt, et al.
Published: (2025)
Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory
by: Fu, Hengyu, et al.
Published: (2024)
by: Fu, Hengyu, et al.
Published: (2024)
Statistical Learning Theory in Lean 4: Empirical Processes from Scratch
by: Zhang, Yuanhe, et al.
Published: (2026)
by: Zhang, Yuanhe, et al.
Published: (2026)
Convergence of Statistical Estimators via Mutual Information Bounds
by: Khribch, El Mahdi, et al.
Published: (2024)
by: Khribch, El Mahdi, et al.
Published: (2024)
Statistical-Computational Trade-offs in Learning Multi-Index Models via Harmonic Analysis
by: Latourelle-Vigeant, Hugo, et al.
Published: (2026)
by: Latourelle-Vigeant, Hugo, et al.
Published: (2026)
Statistical optimal transport
by: Chewi, Sinho, et al.
Published: (2024)
by: Chewi, Sinho, et al.
Published: (2024)
Statistical analysis of Inverse Entropy-regularized Reinforcement Learning
by: Belomestny, Denis, et al.
Published: (2025)
by: Belomestny, Denis, et al.
Published: (2025)
Statistical Learning Guarantees for Group-Invariant Barron Functions
by: Yang, Yahong, et al.
Published: (2025)
by: Yang, Yahong, et al.
Published: (2025)
Statistical Inference and Learning for Shapley Additive Explanations (SHAP)
by: Whitehouse, Justin, et al.
Published: (2026)
by: Whitehouse, Justin, et al.
Published: (2026)
Statistical Inference in Tensor Completion: Optimal Uncertainty Quantification and Statistical-to-Computational Gaps
by: Ma, Wanteng, et al.
Published: (2024)
by: Ma, Wanteng, et al.
Published: (2024)
Complexity Dependent Error Rates for Physics-informed Statistical Learning via the Small-ball Method
by: Marcondes, Diego
Published: (2025)
by: Marcondes, Diego
Published: (2025)
Revisiting Theory of Contrastive Learning for Domain Generalization
by: Alvandi, Ali, et al.
Published: (2025)
by: Alvandi, Ali, et al.
Published: (2025)
Statistical Inference under Performativity
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Statistically guided deep learning
by: Kohler, Michael, et al.
Published: (2025)
by: Kohler, Michael, et al.
Published: (2025)
Statistical and computational challenges in ranking
by: Carpentier, Alexandra, et al.
Published: (2025)
by: Carpentier, Alexandra, et al.
Published: (2025)
Transformers Meet In-Context Learning: A Universal Approximation Theory
by: Li, Gen, et al.
Published: (2025)
by: Li, Gen, et al.
Published: (2025)
Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator
by: Shen, Dennis, et al.
Published: (2023)
by: Shen, Dennis, et al.
Published: (2023)
Statistical inference for pairwise comparison models
by: Han, Ruijian, et al.
Published: (2024)
by: Han, Ruijian, et al.
Published: (2024)
Statistical Inverse Problems in Hilbert Scales
by: Rastogi, Abhishake
Published: (2022)
by: Rastogi, Abhishake
Published: (2022)
Observable Geometry of Singular Statistical Models
by: Plummer, Sean
Published: (2026)
by: Plummer, Sean
Published: (2026)
Statistics of Min-max Normalized Eigenvalues in Random Matrices
by: Nakada, Hyakka, et al.
Published: (2025)
by: Nakada, Hyakka, et al.
Published: (2025)
A Statistical Analysis for Supervised Deep Learning with Exponential Families for Intrinsically Low-dimensional Data
by: Chakraborty, Saptarshi, et al.
Published: (2024)
by: Chakraborty, Saptarshi, et al.
Published: (2024)
Minimax Statistical Estimation under Wasserstein Contamination
by: Chao, Patrick, et al.
Published: (2023)
by: Chao, Patrick, et al.
Published: (2023)
Statistical guarantees for denoising reflected diffusion models
by: Holk, Asbjørn, et al.
Published: (2024)
by: Holk, Asbjørn, et al.
Published: (2024)
Stability and Accuracy Trade-offs in Statistical Estimation
by: Chakraborty, Abhinav, et al.
Published: (2026)
by: Chakraborty, Abhinav, et al.
Published: (2026)
Linear Response Estimators for Singular Statistical Models
by: Elliott, Chris, et al.
Published: (2026)
by: Elliott, Chris, et al.
Published: (2026)
Similar Items
-
A Statistical Theory of Contrastive Pre-training and Multimodal Generative AI
by: Oko, Kazusato, et al.
Published: (2025) -
Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining
by: Lin, Licong, et al.
Published: (2023) -
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models
by: Suh, Namjoon, et al.
Published: (2024) -
Generalized Data Thinning Using Sufficient Statistics
by: Dharamshi, Ameer, et al.
Published: (2023) -
Statistical Learning Theory for Distributional Classification
by: Fiedler, Christian
Published: (2026)