Cover Image

Towards Understanding Feature Learning in Parameter Transfer

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yuan, Hua, Meng, Xuran, Wang, Qiufeng, Xia, Shiyu, Xu, Ning, Yang, Xu, Wang, Jing, Geng, Xin, Rui, Yong
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Enriching Knowledge Distillation with Intra-Class Contrastive Learning
by: Yuan, Hua, et al.
Published: (2025)

GENE-FL: Gene-Driven Parameter-Efficient Dynamic Federated Learning
by: Guo, Shunxin, et al.
Published: (2025)

Learngene Search Across Multiple Datasets for Building Variable-Sized Models
by: Shi, Boyu, et al.
Published: (2026)

Transformer Learns Optimal Variable Selection in Group-Sparse Classification
by: Zhang, Chenyang, et al.
Published: (2025)

Understanding Private Learning From Feature Perspective
by: Ding, Meng, et al.
Published: (2025)

Can Class-Priors Help Single-Positive Multi-Label Learning?
by: Liu, Biao, et al.
Published: (2023)

Transferring Core Knowledge via Learngenes
by: Feng, Fu, et al.
Published: (2024)

Open Continual Feature Selection via Granular-Ball Knowledge Transfer
by: Cao, Xuemei, et al.
Published: (2024)

Reduction-based Pseudo-label Generation for Instance-dependent Partial Label Learning
by: Qiao, Congyu, et al.
Published: (2024)

Preserving Domain Generalization in Fine-Tuning via Joint Parameter Selection
by: Pan, Bin, et al.
Published: (2025)

An Empirical Study of Sample Selection Strategies for Large Language Model Repair
by: Li, Xuran, et al.
Published: (2025)

Inference for Deep Neural Network Estimators in Generalized Nonparametric Models
by: Meng, Xuran, et al.
Published: (2025)

Initialization Matters: On the Benign Overfitting of Two-Layer ReLU CNN with Fully Trainable Layers
by: Shang, Shuning, et al.
Published: (2024)

Towards Understanding Adversarial Transferability in Federated Learning
by: Li, Yijiang, et al.
Published: (2023)

Understanding Forgetting in Continual Learning with Linear Regression
by: Ding, Meng, et al.
Published: (2024)

Perturbation on Feature Coalition: Towards Interpretable Deep Neural Networks
by: Hu, Xuran, et al.
Published: (2024)

Sparse Orthogonal Parameters Tuning for Continual Learning
by: Ning, Kun-Peng, et al.
Published: (2024)

Knowledge Diversion for Efficient Morphology Control and Policy Transfer
by: Feng, Fu, et al.
Published: (2025)

Inaccurate Label Distribution Learning with Dependency Noise
by: Kou, Zhiqiang, et al.
Published: (2024)

Towards Better Performance in Incomplete LDL: Addressing Data Imbalance
by: Kou, Zhiqiang, et al.
Published: (2024)

Beyond Consistency: Inference for the Relative risk functional in Deep Nonparametric Cox Models
by: Ghosal, Sattwik, et al.
Published: (2026)

Is Parameter Collision Hindering Continual Learning in LLMs?
by: Yang, Shuo, et al.
Published: (2024)

Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization
by: Zeng, Dun, et al.
Published: (2024)

Feature Resemblance: Towards a Theoretical Understanding of Analogical Reasoning in Transformers
by: Xu, Ruichen, et al.
Published: (2026)

Towards Understanding the Benefit of Multitask Representation Learning in Decision Process
by: Lu, Rui, et al.
Published: (2025)

Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning
by: Wang, Qi, et al.
Published: (2025)

One-shot Transfer Learning for Population Mapping
by: Shao, Erzhuo, et al.
Published: (2021)

Understanding Adversarial Robustness from Feature Maps of Convolutional Layers
by: Xu, Cong, et al.
Published: (2022)

Towards Understanding Transformers in Learning Random Walks
by: Shi, Wei, et al.
Published: (2025)

Understanding Knowledge Transferability for Transfer Learning: A Survey
by: Wang, Haohua, et al.
Published: (2025)

Meta-Aligner: Bidirectional Preference-Policy Optimization for Multi-Objective LLMs Alignment
by: Xu, Wenzhe, et al.
Published: (2026)

Parameter Identification for Partial Differential Equation with Jump Discontinuities in Coefficients by Markov Switching Model and Physics-Informed Machine Learning
by: Zhang, Zhikun, et al.
Published: (2025)

Cross-Modal Domain Adaptation in Brain Disease Diagnosis: Maximum Mean Discrepancy-based Convolutional Neural Networks
by: Zhu, Xuran
Published: (2024)

A Unified Framework for Knowledge Transfer in Bidirectional Model Scaling
by: Shen, Jianlu, et al.
Published: (2026)

Transfer Learning for Classification under Decision Rule Drift with Application to Optimal Individualized Treatment Rule Estimation
by: Wang, Xiaohan, et al.
Published: (2025)

STHFL: Spatio-Temporal Heterogeneous Federated Learning
by: Guo, Shunxin, et al.
Published: (2025)

GRASP: Replace Redundant Layers with Adaptive Singular Parameters for Efficient Model Compression
by: Liu, Kainan, et al.
Published: (2024)

Understanding Task Vectors in In-Context Learning: Emergence, Functionality, and Limitations
by: Dong, Yuxin, et al.
Published: (2025)

DivControl: Knowledge Diversion for Controllable Image Generation
by: Xie, Yucheng, et al.
Published: (2025)

Self-Supervised Weight Templates for Scalable Vision Model Initialization
by: Xie, Yucheng, et al.
Published: (2026)