:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Liu, Renpu, Shen, Cong, Yang, Jing
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2406.04596
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery
por: Liu, Renpu, et al.
Publicado: (2024)

Unlabeled Data Can Provably Enhance In-Context Learning of Transformers
por: Liu, Renpu, et al.
Publicado: (2026)

A Shared Low-Rank Adaptation Approach to Personalized RLHF
por: Liu, Renpu, et al.
Publicado: (2025)

MUSO: Achieving Exact Machine Unlearning in Over-Parameterized Regimes
por: Yang, Ruikai, et al.
Publicado: (2024)

In-Context Learning Under Regime Change
por: Dudley, Carson, et al.
Publicado: (2026)

Harnessing the Power of Federated Learning in Federated Contextual Bandits
por: Shi, Chengshuai, et al.
Publicado: (2023)

Lean Clients, Full Accuracy: Hybrid Zeroth- and First-Order Split Federated Learning
por: Kou, Zhoubin, et al.
Publicado: (2026)

Decision Feedback In-Context Learning for Wireless Symbol Detection
por: Fan, Li, et al.
Publicado: (2025)

Criteria and Bias of Parameterized Linear Regression under Edge of Stability Regime
por: Zhang, Peiyuan, et al.
Publicado: (2024)

Mild Over-Parameterization Benefits Asymmetric Tensor PCA
por: Ding, Shihong, et al.
Publicado: (2026)

Federated Split Learning with Improved Communication and Storage Efficiency
por: Mu, Yujia, et al.
Publicado: (2025)

Personalized Federated Learning with Attention-based Client Selection
por: Chen, Zihan, et al.
Publicado: (2023)

Average Reward Reinforcement Learning for Wireless Radio Resource Management
por: Yang, Kun, et al.
Publicado: (2025)

General Machine Learning: Theory for Learning Under Variable Regimes
por: Osmani, Aomar
Publicado: (2026)

Parameterizing Federated Continual Learning for Reproducible Research
por: Cox, Bart, et al.
Publicado: (2024)

Accelerating Hybrid Federated Learning Convergence under Partial Participation
por: Bian, Jieming, et al.
Publicado: (2023)

HeteroSample: Meta-path Guided Sampling for Heterogeneous Graph Representation Learning
por: Liu, Ao, et al.
Publicado: (2024)

Secure Vertical Federated Learning Under Unreliable Connectivity
por: Qiu, Xinchi, et al.
Publicado: (2023)

On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
por: Shen, Wei, et al.
Publicado: (2024)

Fairness Under Demographic Scarce Regime
por: Kenfack, Patrik Joslin, et al.
Publicado: (2023)

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression
por: Ding, Shihong, et al.
Publicado: (2025)

Representation Learning for Regime detection in Block Hierarchical Financial Markets
por: Orton, Alexa, et al.
Publicado: (2024)

Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise
por: Khanal, Bikram, et al.
Publicado: (2024)

Federated Prompt Learning for Weather Foundation Models on Devices
por: Chen, Shengchao, et al.
Publicado: (2023)

Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime
por: Shilton, Alistair, et al.
Publicado: (2024)

Explainable Learning Rate Regimes for Stochastic Optimization
por: Yang, Zhuang
Publicado: (2025)

FedLED: Label-Free Equipment Fault Diagnosis with Vertical Federated Transfer Learning
por: Shen, Jie, et al.
Publicado: (2023)

An Autoencoder-Based Constellation Design for AirComp in Wireless Federated Learning
por: Mu, Yujia, et al.
Publicado: (2024)

KAN-FIF: Spline-Parameterized Lightweight Physics-based Tropical Cyclone Estimation on Meteorological Satellite
por: Shen, Jiakang, et al.
Publicado: (2026)

Learning Extrinsic Dexterity with Parameterized Manipulation Primitives
por: Yang, Shih-Min, et al.
Publicado: (2023)

Decision Feedback In-Context Symbol Detection over Block-Fading Channels
por: Fan, Li, et al.
Publicado: (2024)

Disentangled Representation Learning via Flow Matching
por: Chi, Jinjin, et al.
Publicado: (2026)

Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization
por: Choi, Hongjun, et al.
Publicado: (2024)

FedCross: Intertemporal Federated Learning Under Evolutionary Games
por: Lu, Jianfeng, et al.
Publicado: (2024)

Federated Learning for Diffusion Models
por: Peng, Zihao, et al.
Publicado: (2025)

Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
por: Shen, Wei, et al.
Publicado: (2023)

Robust Multimodal Representation Learning in Healthcare
por: Zhu, Xiaoguang, et al.
Publicado: (2026)

Do Physics Foundation Models Learn Generalizable Physics? A Bias-Aware Benchmark Across Physical Regimes and Distribution Shifts
por: Chu, Mengdi, et al.
Publicado: (2026)

Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
por: Gao, Fengyu, et al.
Publicado: (2024)

Federated Contrastive Learning of Graph-Level Representations
por: Li, Xiang, et al.
Publicado: (2024)