Meta-Learning from Learning Curves for Budget-Limited Algorithm Selection
Fuente:
arXiv
Guardado en:
| Autores principales: | Nguyen, Manh Hung, Sun-Hosoya, Lisheng, Guyon, Isabelle |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Data-Efficient and Robust Task Selection for Meta-Learning
por: Zhan, Donglin, et al.
Publicado: (2024)
por: Zhan, Donglin, et al.
Publicado: (2024)
A New First-Order Meta-Learning Algorithm with Convergence Guarantees
por: Chayti, El Mahdi, et al.
Publicado: (2024)
por: Chayti, El Mahdi, et al.
Publicado: (2024)
Coreset-Based Task Selection for Sample-Efficient Meta-Reinforcement Learning
por: Zhan, Donglin, et al.
Publicado: (2025)
por: Zhan, Donglin, et al.
Publicado: (2025)
Solving Truly Massive Budgeted Monotonic POMDPs with Oracle-Guided Meta-Reinforcement Learning
por: Vora, Manav, et al.
Publicado: (2024)
por: Vora, Manav, et al.
Publicado: (2024)
AdaSwitch: An Adaptive Switching Meta-Algorithm for Learning-Augmented Bounded-Influence Problems
por: Chen, Xi, et al.
Publicado: (2025)
por: Chen, Xi, et al.
Publicado: (2025)
Series Expansion of Probability of Correct Selection for Improved Finite Budget Allocation in Ranking and Selection
por: Shi, Xinbo, et al.
Publicado: (2024)
por: Shi, Xinbo, et al.
Publicado: (2024)
The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
por: Collins-Woodfin, Elizabeth, et al.
Publicado: (2024)
por: Collins-Woodfin, Elizabeth, et al.
Publicado: (2024)
From Learning to Optimize to Learning Optimization Algorithms
por: Castera, Camille, et al.
Publicado: (2024)
por: Castera, Camille, et al.
Publicado: (2024)
Memory-Reduced Meta-Learning with Guaranteed Convergence
por: Yang, Honglin, et al.
Publicado: (2024)
por: Yang, Honglin, et al.
Publicado: (2024)
Faster Adaptive Decentralized Learning Algorithms
por: Huang, Feihu, et al.
Publicado: (2024)
por: Huang, Feihu, et al.
Publicado: (2024)
Central Limit Theorems for Asynchronous Averaged Q-Learning
por: Liu, Xingtu
Publicado: (2025)
por: Liu, Xingtu
Publicado: (2025)
Coverage-Validity-Aware Algorithmic Recourse
por: Bui, Ngoc, et al.
Publicado: (2023)
por: Bui, Ngoc, et al.
Publicado: (2023)
Meta-Learning for Physically-Constrained Neural System Identification
por: Chakrabarty, Ankush, et al.
Publicado: (2025)
por: Chakrabarty, Ankush, et al.
Publicado: (2025)
How to Set $β_1, β_2$ in Adam: An Online Learning Perspective
por: Nguyen, Quan
Publicado: (2025)
por: Nguyen, Quan
Publicado: (2025)
Online Learning and Optimization for Queues with Unknown Demand Curve and Service Distribution
por: Chen, Xinyun, et al.
Publicado: (2023)
por: Chen, Xinyun, et al.
Publicado: (2023)
Contextual Bandits with Budgeted Information Reveal
por: Gan, Kyra, et al.
Publicado: (2023)
por: Gan, Kyra, et al.
Publicado: (2023)
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
por: Tran-The, Hung, et al.
Publicado: (2022)
por: Tran-The, Hung, et al.
Publicado: (2022)
A Semantic-Loss Function Modeling Framework With Task-Oriented Machine Learning Perspectives
por: Nguyen, Ti Ti, et al.
Publicado: (2025)
por: Nguyen, Ti Ti, et al.
Publicado: (2025)
Learning Algorithm Hyperparameters for Fast Parametric Convex Optimization
por: Sambharya, Rajiv, et al.
Publicado: (2024)
por: Sambharya, Rajiv, et al.
Publicado: (2024)
Mitigating Forgetting in Continual Learning with Selective Gradient Projection
por: Singh, Anika, et al.
Publicado: (2026)
por: Singh, Anika, et al.
Publicado: (2026)
Mathematical Programming Algorithms for Convex Hull Approximation with a Hyperplane Budget
por: Barbato, Michele, et al.
Publicado: (2024)
por: Barbato, Michele, et al.
Publicado: (2024)
FedGiA: An Efficient Hybrid Algorithm for Federated Learning
por: Zhou, Shenglong, et al.
Publicado: (2022)
por: Zhou, Shenglong, et al.
Publicado: (2022)
UVIP: Model-Free Approach to Evaluate Reinforcement Learning Algorithms
por: Belomestny, Denis, et al.
Publicado: (2021)
por: Belomestny, Denis, et al.
Publicado: (2021)
Model-Free Learning for the Linear Quadratic Regulator over Rate-Limited Channels
por: Ye, Lintao, et al.
Publicado: (2024)
por: Ye, Lintao, et al.
Publicado: (2024)
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning
por: Hu, Yifan, et al.
Publicado: (2020)
por: Hu, Yifan, et al.
Publicado: (2020)
Learning in Inverse Optimization: Incenter Cost, Augmented Suboptimality Loss, and Algorithms
por: Scroccaro, Pedro Zattoni, et al.
Publicado: (2023)
por: Scroccaro, Pedro Zattoni, et al.
Publicado: (2023)
A Theoretical and Experimental Study of a Novel Adaptive Learning Algorithm
por: Kumari, Sakshi, et al.
Publicado: (2026)
por: Kumari, Sakshi, et al.
Publicado: (2026)
Are Convex Optimization Curves Convex?
por: Barzilai, Guy, et al.
Publicado: (2025)
por: Barzilai, Guy, et al.
Publicado: (2025)
Learning to Shuffle: Block Reshuffling and Reversal Schemes for Stochastic Optimization
por: Nguyen, Lam M., et al.
Publicado: (2026)
por: Nguyen, Lam M., et al.
Publicado: (2026)
Shuffling Momentum Gradient Algorithm for Convex Optimization
por: Tran, Trang H., et al.
Publicado: (2024)
por: Tran, Trang H., et al.
Publicado: (2024)
Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networks
por: Nguyen, Duong Thuy Anh, et al.
Publicado: (2024)
por: Nguyen, Duong Thuy Anh, et al.
Publicado: (2024)
Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits
por: Maity, Sreejeet, et al.
Publicado: (2025)
por: Maity, Sreejeet, et al.
Publicado: (2025)
A Minibatch-SGD-Based Learning Meta-Policy for Inventory Systems with Myopic Optimal Policy
por: Lyu, Jiameng, et al.
Publicado: (2024)
por: Lyu, Jiameng, et al.
Publicado: (2024)
Adaptive Moment Estimation Optimization Algorithm Using Projection Gradient for Deep Learning
por: Li, Yongqi, et al.
Publicado: (2025)
por: Li, Yongqi, et al.
Publicado: (2025)
Hierarchical Deep Reinforcement Learning Framework for Multi-Year Asset Management Under Budget Constraints
por: Fard, Amir, et al.
Publicado: (2025)
por: Fard, Amir, et al.
Publicado: (2025)
Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for Model-free LQR
por: Toso, Leonardo F., et al.
Publicado: (2024)
por: Toso, Leonardo F., et al.
Publicado: (2024)
Risk-Sensitive Q-Learning in Continuous Time with Application to Dynamic Portfolio Selection
por: Xie, Chuhan
Publicado: (2025)
por: Xie, Chuhan
Publicado: (2025)
A Reinforcement-Learning-Based Multiple-Column Selection Strategy for Column Generation
por: Yuan, Haofeng, et al.
Publicado: (2023)
por: Yuan, Haofeng, et al.
Publicado: (2023)
State Estimation Using Particle Filtering in Adaptive Machine Learning Methods: Integrating Q-Learning and NEAT Algorithms with Noisy Radar Measurements
por: Song, Wonjin, et al.
Publicado: (2025)
por: Song, Wonjin, et al.
Publicado: (2025)
Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty
por: Lin, Zikun, et al.
Publicado: (2026)
por: Lin, Zikun, et al.
Publicado: (2026)
Ejemplares similares
-
Data-Efficient and Robust Task Selection for Meta-Learning
por: Zhan, Donglin, et al.
Publicado: (2024) -
A New First-Order Meta-Learning Algorithm with Convergence Guarantees
por: Chayti, El Mahdi, et al.
Publicado: (2024) -
Coreset-Based Task Selection for Sample-Efficient Meta-Reinforcement Learning
por: Zhan, Donglin, et al.
Publicado: (2025) -
Solving Truly Massive Budgeted Monotonic POMDPs with Oracle-Guided Meta-Reinforcement Learning
por: Vora, Manav, et al.
Publicado: (2024) -
AdaSwitch: An Adaptive Switching Meta-Algorithm for Learning-Augmented Bounded-Influence Problems
por: Chen, Xi, et al.
Publicado: (2025)