Towards Fundamental Limits for Active Multi-distribution Learning
Fuente:
arXiv
Guardado en:
| Autores principales: | Zhang, Chicheng, Zhou, Yihan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach
por: Li, Yinan, et al.
Publicado: (2023)
por: Li, Yinan, et al.
Publicado: (2023)
Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms
por: Li, Yichen, et al.
Publicado: (2023)
por: Li, Yichen, et al.
Publicado: (2023)
Interactive and Hybrid Imitation Learning: Provably Beating Behavior Cloning
por: Li, Yichen, et al.
Publicado: (2024)
por: Li, Yichen, et al.
Publicado: (2024)
Bridging Lifelong and Multi-Task Representation Learning via Algorithm and Complexity Measure
por: Wang, Zhi, et al.
Publicado: (2025)
por: Wang, Zhi, et al.
Publicado: (2025)
Beyond Task Diversity: Provable Representation Transfer for Sequential Multi-Task Linear Bandits
por: Duong, Thang, et al.
Publicado: (2025)
por: Duong, Thang, et al.
Publicado: (2025)
Taming the Monster Every Context: Complexity Measure and Unified Framework for Offline-Oracle Efficient Contextual Bandits
por: Qin, Hao, et al.
Publicado: (2026)
por: Qin, Hao, et al.
Publicado: (2026)
Improving the Data-efficiency of Reinforcement Learning by Warm-starting with LLM
por: Duong, Thang, et al.
Publicado: (2025)
por: Duong, Thang, et al.
Publicado: (2025)
Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards
por: Qin, Hao, et al.
Publicado: (2023)
por: Qin, Hao, et al.
Publicado: (2023)
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
por: Zhang, Yihan, et al.
Publicado: (2024)
por: Zhang, Yihan, et al.
Publicado: (2024)
A Competitive Algorithm for Agnostic Active Learning
por: Price, Eric, et al.
Publicado: (2023)
por: Price, Eric, et al.
Publicado: (2023)
Towards Multimodal Active Learning: Efficient Learning with Limited Paired Data
por: Zhang, Jiancheng, et al.
Publicado: (2025)
por: Zhang, Jiancheng, et al.
Publicado: (2025)
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
por: Jang, Kyoungseok, et al.
Publicado: (2024)
por: Jang, Kyoungseok, et al.
Publicado: (2024)
Near-Polynomially Competitive Active Logistic Regression
por: Zhou, Yihan, et al.
Publicado: (2025)
por: Zhou, Yihan, et al.
Publicado: (2025)
High Effort, Low Gain: Fundamental Limits of Active Learning for Linear Dynamical Systems
por: Chatzikiriakos, Nicolas, et al.
Publicado: (2025)
por: Chatzikiriakos, Nicolas, et al.
Publicado: (2025)
The Fundamental Limits of Least-Privilege Learning
por: Stadler, Theresa, et al.
Publicado: (2024)
por: Stadler, Theresa, et al.
Publicado: (2024)
Physics-Informed Parametric Bandits for Beam Alignment in mmWave Communications
por: Qin, Hao, et al.
Publicado: (2025)
por: Qin, Hao, et al.
Publicado: (2025)
Achieving adaptivity and optimality for multi-armed bandits using Exponential-Kullback Leibler Maillard Sampling
por: Qin, Hao, et al.
Publicado: (2025)
por: Qin, Hao, et al.
Publicado: (2025)
Fundamental Limits of Learning High-dimensional Simplices in Noisy Regimes
por: Saberi, Seyed Amir Hossein, et al.
Publicado: (2025)
por: Saberi, Seyed Amir Hossein, et al.
Publicado: (2025)
Fundamental Limits of Perfect Concept Erasure
por: Chowdhury, Somnath Basu Roy, et al.
Publicado: (2025)
por: Chowdhury, Somnath Basu Roy, et al.
Publicado: (2025)
Towards Comparable Active Learning
por: Werner, Thorben, et al.
Publicado: (2023)
por: Werner, Thorben, et al.
Publicado: (2023)
Fundamental Limits of Membership Inference Attacks on Machine Learning Models
por: Aubinais, Eric, et al.
Publicado: (2023)
por: Aubinais, Eric, et al.
Publicado: (2023)
Exploring Topological Bias in Heterogeneous Graph Neural Networks
por: Zhang, Yihan
Publicado: (2025)
por: Zhang, Yihan
Publicado: (2025)
The Fundamental Limits of Fraud Detection in Card Payment Networks
por: Dhama, Gaurav
Publicado: (2026)
por: Dhama, Gaurav
Publicado: (2026)
No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
por: Wu, Changlong, et al.
Publicado: (2024)
por: Wu, Changlong, et al.
Publicado: (2024)
Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms
por: Zhang, Qining, et al.
Publicado: (2023)
por: Zhang, Qining, et al.
Publicado: (2023)
How Sparse Can We Prune A Deep Network: A Fundamental Limit Perspective
por: Zhang, Qiaozhe, et al.
Publicado: (2023)
por: Zhang, Qiaozhe, et al.
Publicado: (2023)
Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits
por: Chen, Fan, et al.
Publicado: (2025)
por: Chen, Fan, et al.
Publicado: (2025)
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss
por: Getu, Tilahun M., et al.
Publicado: (2023)
por: Getu, Tilahun M., et al.
Publicado: (2023)
Fundamental Limits of Man-in-the-Middle Attack Detection in Model-Free Reinforcement Learning
por: Rani, Rishi, et al.
Publicado: (2026)
por: Rani, Rishi, et al.
Publicado: (2026)
Towards a Foundation Model for Physics-Informed Neural Networks: Multi-PDE Learning with Active Sampling
por: Park, Keon Vin
Publicado: (2025)
por: Park, Keon Vin
Publicado: (2025)
Toward Information Theoretic Active Inverse Reinforcement Learning
por: Bajgar, Ondrej, et al.
Publicado: (2024)
por: Bajgar, Ondrej, et al.
Publicado: (2024)
High-Dimensional Partial Least Squares: Spectral Analysis and Fundamental Limitations
por: Léger, Victor, et al.
Publicado: (2025)
por: Léger, Victor, et al.
Publicado: (2025)
The Verification Tax: Fundamental Limits of AI Auditing in the Rare-Error Regime
por: Wang, Jason Z
Publicado: (2026)
por: Wang, Jason Z
Publicado: (2026)
Falcon: Fair Active Learning using Multi-armed Bandits
por: Tae, Ki Hyun, et al.
Publicado: (2024)
por: Tae, Ki Hyun, et al.
Publicado: (2024)
Cross-Treatment Effect Estimation for Multi-Category, Multi-Valued Causal Inference via Dynamic Neural Masking
por: Ke, Xiaopeng, et al.
Publicado: (2025)
por: Ke, Xiaopeng, et al.
Publicado: (2025)
Fundamental Limitations on Subquadratic Alternatives to Transformers
por: Alman, Josh, et al.
Publicado: (2024)
por: Alman, Josh, et al.
Publicado: (2024)
Fundamental Limitations in Pointwise Defences of LLM Finetuning APIs
por: Davies, Xander, et al.
Publicado: (2025)
por: Davies, Xander, et al.
Publicado: (2025)
The Fundamental Limits of Structure-Agnostic Functional Estimation
por: Balakrishnan, Sivaraman, et al.
Publicado: (2023)
por: Balakrishnan, Sivaraman, et al.
Publicado: (2023)
Mind Dreamer: Untethering Imagination via Active Causal Intervention on Latent Manifolds
por: Xu, Shaojun, et al.
Publicado: (2026)
por: Xu, Shaojun, et al.
Publicado: (2026)
Epistemic Throughput: Fundamental Limits of Attention-Constrained Inference
por: You, Lei
Publicado: (2026)
por: You, Lei
Publicado: (2026)
Ejemplares similares
-
Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach
por: Li, Yinan, et al.
Publicado: (2023) -
Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms
por: Li, Yichen, et al.
Publicado: (2023) -
Interactive and Hybrid Imitation Learning: Provably Beating Behavior Cloning
por: Li, Yichen, et al.
Publicado: (2024) -
Bridging Lifelong and Multi-Task Representation Learning via Algorithm and Complexity Measure
por: Wang, Zhi, et al.
Publicado: (2025) -
Beyond Task Diversity: Provable Representation Transfer for Sequential Multi-Task Linear Bandits
por: Duong, Thang, et al.
Publicado: (2025)