Copertina

ColA: Collaborative Adaptation with Gradient Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Diao, Enmao, Le, Qi, Wu, Suya, Wang, Xinran, Anwar, Ali, Ding, Jie, Tarokh, Vahid
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

DynamicFL: Federated Learning with Dynamic Communication Resource Allocation
di: Le, Qi, et al.
Pubblicazione: (2024)

Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing
di: Le, Qi, et al.
Pubblicazione: (2025)

Robust Score-Based Quickest Change Detection
di: Moushegian, Sean, et al.
Pubblicazione: (2024)

MAP: Multi-Human-Value Alignment Palette
di: Wang, Xinran, et al.
Pubblicazione: (2024)

Parabolic Continual Learning
di: Yang, Haoming, et al.
Pubblicazione: (2025)

Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes
di: Yang, Haoming, et al.
Pubblicazione: (2024)

Elliptic Loss Regularization
di: Hasan, Ali, et al.
Pubblicazione: (2025)

Perceiver-based CDF Modeling for Time Series Forecasting
di: Le, Cat P., et al.
Pubblicazione: (2023)

Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
di: Sheng, Zhecheng, et al.
Pubblicazione: (2025)

Graph Tokenization for Bridging Graphs and Transformers
di: Guo, Zeyuan, et al.
Pubblicazione: (2026)

IP-FL: Incentivized and Personalized Federated Learning
di: Khan, Ahmad Faraz, et al.
Pubblicazione: (2023)

Boosting In-Context Learning in LLMs Through the Lens of Classical Supervised Learning
di: Gundem, Korel, et al.
Pubblicazione: (2025)

Neuro-Logic Lifelong Learning
di: He, Bowen, et al.
Pubblicazione: (2025)

Learning in Context, Guided by Choice: A Reward-Free Paradigm for Reinforcement Learning with Transformers
di: Dong, Juncheng, et al.
Pubblicazione: (2026)

A PDE-Informed Latent Diffusion Model for 2-m Temperature Downscaling
di: Rosu, Paul, et al.
Pubblicazione: (2025)

Think Before You Prune: Self-Reflective Structured Pruning for Reasoning Language Models
di: Wang, Ziyan, et al.
Pubblicazione: (2025)

CARE: Turning LLMs Into Causal Reasoning Expert
di: Dong, Juncheng, et al.
Pubblicazione: (2025)

From Local to Global: Revisiting Structured Pruning Paradigms for Large Language Models
di: Wang, Ziyan, et al.
Pubblicazione: (2025)

A Kinetic Energy Perspective of Flow Matching
di: Li, Ziyun, et al.
Pubblicazione: (2026)

CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning
di: Hossen, Md Anwar, et al.
Pubblicazione: (2026)

FedOBP: Federated Optimal Brain Personalization through Cloud-Edge Element-wise Decoupling
di: Chen, Xingyan, et al.
Pubblicazione: (2026)

Accelerating LLM Reasoning via Early Rejection with Partial Reward Modeling
di: Cheshmi, Seyyed Saeid, et al.
Pubblicazione: (2025)

Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions
di: Kuiper, Patrick, et al.
Pubblicazione: (2024)

Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent
di: Kumar, Mohit, et al.
Pubblicazione: (2024)

Large Deviation Analysis of Score-based Hypothesis Testing
di: Diao, Enmao, et al.
Pubblicazione: (2024)

Evaluating Robustness of Reinforcement Learning Algorithms for Autonomous Shipping
di: Lesy, Bavo, et al.
Pubblicazione: (2024)

Robust Model-Based Reinforcement Learning with an Adversarial Auxiliary Model
di: Herremans, Siemen, et al.
Pubblicazione: (2024)

Randomness and Interpolation Improve Gradient Descent
di: Li, Jiawen, et al.
Pubblicazione: (2025)

Federated Nested Learning: Collaborative Training of Self-Referential Memories for Test-Time Adaptation
di: Chen, Hong, et al.
Pubblicazione: (2026)

Asymptotically Optimal Change Detection for Unnormalized Pre- and Post-Change Distributions
di: Adibi, Arman, et al.
Pubblicazione: (2024)

GAC: Stabilizing Asynchronous RL Training for LLMs via Gradient Alignment Control
di: Xu, Haofeng, et al.
Pubblicazione: (2026)

Consolidation or Adaptation? PRISM: Disentangling SFT and RL Data via Gradient Concentration
di: Zhao, Yang, et al.
Pubblicazione: (2026)

Transfer Learning for Bayesian Optimization on Heterogeneous Search Spaces
di: Fan, Zhou, et al.
Pubblicazione: (2023)

Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation
di: Zhang, Zhen, et al.
Pubblicazione: (2024)

Energy-Structured Low-Rank Adaptation for Continual Learning
di: Li, Longhua, et al.
Pubblicazione: (2026)

Training Data Selection with Gradient Orthogonality for Efficient Domain Adaptation
di: Zhang, Xiyang, et al.
Pubblicazione: (2026)

Inference-Time Alignment Control for Diffusion Models with Reinforcement Learning Guidance
di: Jin, Luozhijie, et al.
Pubblicazione: (2025)

Teleportation With Null Space Gradient Projection for Optimization Acceleration
di: Wu, Zihao, et al.
Pubblicazione: (2025)

Learn2Mix: Training Neural Networks Using Adaptive Data Integration
di: Venkatasubramanian, Shyam, et al.
Pubblicazione: (2024)

A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning
di: Feng, Xidong, et al.
Pubblicazione: (2021)