On Hypothesis Transfer Learning of Functional Linear Models
Fuente:
arXiv
Saved in:
| Main Authors: | Lin, Haotian, Reimherr, Matthew |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Smoothness Adaptive Hypothesis Transfer Learning
by: Lin, Haotian, et al.
Published: (2024)
by: Lin, Haotian, et al.
Published: (2024)
Model-Robust and Adaptive-Optimal Transfer Learning for Tackling Concept Shifts in Nonparametric Regression
by: Lin, Haotian, et al.
Published: (2025)
by: Lin, Haotian, et al.
Published: (2025)
Pure Differential Privacy for Functional Summaries with a Laplace-like Process
by: Lin, Haotian, et al.
Published: (2023)
by: Lin, Haotian, et al.
Published: (2023)
FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions
by: Boschi, Tobia, et al.
Published: (2023)
by: Boschi, Tobia, et al.
Published: (2023)
Harnessing Vision-Language Models for Time Series Anomaly Detection
by: He, Zelin, et al.
Published: (2025)
by: He, Zelin, et al.
Published: (2025)
The Master Key Hypothesis: Unlocking Cross-Model Capability Transfer via Linear Subspace Alignment
by: Balasubramanian, Rishab, et al.
Published: (2026)
by: Balasubramanian, Rishab, et al.
Published: (2026)
Linear Representation Transferability Hypothesis: Leveraging Small Models to Steer Large Models
by: Bello, Femi, et al.
Published: (2025)
by: Bello, Femi, et al.
Published: (2025)
ReSkill: Reconciling Skill Creation with Policy Optimization in Agentic RL
by: He, Zelin, et al.
Published: (2026)
by: He, Zelin, et al.
Published: (2026)
Universality in Transfer Learning for Linear Models
by: Ghane, Reza, et al.
Published: (2024)
by: Ghane, Reza, et al.
Published: (2024)
Coefficient Shape Transfer Learning for Functional Linear Regression
by: Jiao, Shuhao, et al.
Published: (2025)
by: Jiao, Shuhao, et al.
Published: (2025)
The Linear Centroids Hypothesis: Features as Directions Learned by Local Experts
by: Walker, Thomas, et al.
Published: (2026)
by: Walker, Thomas, et al.
Published: (2026)
Linear Convergence of Diffusion Models Under the Manifold Hypothesis
by: Potaptchik, Peter, et al.
Published: (2024)
by: Potaptchik, Peter, et al.
Published: (2024)
In-Context Learning with Hypothesis-Class Guidance
by: Lin, Ziqian, et al.
Published: (2025)
by: Lin, Ziqian, et al.
Published: (2025)
Unified Transfer Learning Models in High-Dimensional Linear Regression
by: Liu, Shuo Shuo
Published: (2023)
by: Liu, Shuo Shuo
Published: (2023)
Comparative Evaluation of Learning Models for Bionic Robots: Non-Linear Transfer Function Identifications
by: Hsieh, Po-Yu, et al.
Published: (2024)
by: Hsieh, Po-Yu, et al.
Published: (2024)
Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation
by: Soto, Carlos, et al.
Published: (2024)
by: Soto, Carlos, et al.
Published: (2024)
M$^2$AD: Multi-Sensor Multi-System Anomaly Detection through Global Scoring and Calibrated Thresholding
by: Alnegheimish, Sarah, et al.
Published: (2025)
by: Alnegheimish, Sarah, et al.
Published: (2025)
The Linear Representation Hypothesis and the Geometry of Large Language Models
by: Park, Kiho, et al.
Published: (2023)
by: Park, Kiho, et al.
Published: (2023)
The Effect of Depth on the Expressivity of Deep Linear State-Space Models
by: Bao, Zeyu, et al.
Published: (2025)
by: Bao, Zeyu, et al.
Published: (2025)
Expectation Error Bounds for Transfer Learning in Linear Regression and Linear Neural Networks
by: Liu, Meitong, et al.
Published: (2026)
by: Liu, Meitong, et al.
Published: (2026)
Automatic Cross-Domain Transfer Learning for Linear Regression
by: Liu, Xinshun, et al.
Published: (2020)
by: Liu, Xinshun, et al.
Published: (2020)
TransferTraj: A Vehicle Trajectory Learning Model for Region and Task Transferability
by: Wei, Tonglong, et al.
Published: (2025)
by: Wei, Tonglong, et al.
Published: (2025)
Numerical Investigation of Sequence Modeling Theory using Controllable Memory Functions
by: Jiang, Haotian, et al.
Published: (2025)
by: Jiang, Haotian, et al.
Published: (2025)
Nonstationary Reinforcement Learning with Linear Function Approximation
by: Zhou, Huozhi, et al.
Published: (2020)
by: Zhou, Huozhi, et al.
Published: (2020)
Replicable Reinforcement Learning with Linear Function Approximation
by: Eaton, Eric, et al.
Published: (2025)
by: Eaton, Eric, et al.
Published: (2025)
Forecast Sports Outcomes under Efficient Market Hypothesis: Theoretical and Experimental Analysis of Odds-Only and Generalised Linear Models
by: Goto, Kaito, et al.
Published: (2026)
by: Goto, Kaito, et al.
Published: (2026)
Distributionally Robust Online Markov Game with Linear Function Approximation
by: Zheng, Zewu, et al.
Published: (2025)
by: Zheng, Zewu, et al.
Published: (2025)
Deep Transfer Learning: Model Framework and Error Analysis
by: Jiao, Yuling, et al.
Published: (2024)
by: Jiao, Yuling, et al.
Published: (2024)
When to Transfer: Adaptive Source Selection for Positive Transfer in Linear Models
by: Cherkaoui, Hamza, et al.
Published: (2025)
by: Cherkaoui, Hamza, et al.
Published: (2025)
Transfer Learning of Linear Regression with Multiple Pretrained Models: Benefiting from More Pretrained Models via Overparameterization Debiasing
by: Boharon, Daniel, et al.
Published: (2026)
by: Boharon, Daniel, et al.
Published: (2026)
Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation
by: Vargas, Francisco, et al.
Published: (2020)
by: Vargas, Francisco, et al.
Published: (2020)
On Global Applicability and Location Transferability of Generative Deep Learning Models for Precipitation Downscaling
by: Harder, Paula, et al.
Published: (2025)
by: Harder, Paula, et al.
Published: (2025)
Learning and Transferring Sparse Contextual Bigrams with Linear Transformers
by: Ren, Yunwei, et al.
Published: (2024)
by: Ren, Yunwei, et al.
Published: (2024)
Reinforcement Learning with Function Approximation: From Linear to Nonlinear
by: Long, Jihao, et al.
Published: (2023)
by: Long, Jihao, et al.
Published: (2023)
Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
by: Cheng, Xiang, et al.
Published: (2023)
by: Cheng, Xiang, et al.
Published: (2023)
Hypothesis Spaces for Deep Learning
by: Wang, Rui, et al.
Published: (2024)
by: Wang, Rui, et al.
Published: (2024)
Heterogeneous Transfer Learning for Building High-Dimensional Generalized Linear Models with Disparate Datasets
by: Zhao, Ruzhang, et al.
Published: (2023)
by: Zhao, Ruzhang, et al.
Published: (2023)
Transferring Linear Features Across Language Models With Model Stitching
by: Chen, Alan, et al.
Published: (2025)
by: Chen, Alan, et al.
Published: (2025)
SenTSR-Bench: Thinking with Injected Knowledge for Time-Series Reasoning
by: He, Zelin, et al.
Published: (2026)
by: He, Zelin, et al.
Published: (2026)
Statistical Inference for Temporal Difference Learning with Linear Function Approximation
by: Wu, Weichen, et al.
Published: (2024)
by: Wu, Weichen, et al.
Published: (2024)
Similar Items
-
Smoothness Adaptive Hypothesis Transfer Learning
by: Lin, Haotian, et al.
Published: (2024) -
Model-Robust and Adaptive-Optimal Transfer Learning for Tackling Concept Shifts in Nonparametric Regression
by: Lin, Haotian, et al.
Published: (2025) -
Pure Differential Privacy for Functional Summaries with a Laplace-like Process
by: Lin, Haotian, et al.
Published: (2023) -
FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions
by: Boschi, Tobia, et al.
Published: (2023) -
Harnessing Vision-Language Models for Time Series Anomaly Detection
by: He, Zelin, et al.
Published: (2025)