Cover Image

Scalable Meta-Learning via Mixed-Mode Differentiation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kemaev, Iurii, Calian, Dan A, Zintgraf, Luisa M, Farquhar, Gregory, van Hasselt, Hado
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DataRater: Meta-Learned Dataset Curation
by: Calian, Dan A., et al.
Published: (2025)

General Uncertainty Estimation with Delta Variances
by: Schmitt, Simon, et al.
Published: (2025)

A Survey of Temporal Credit Assignment in Deep Reinforcement Learning
by: Pignatelli, Eduardo, et al.
Published: (2023)

Normalization and effective learning rates in reinforcement learning
by: Lyle, Clare, et al.
Published: (2024)

Wasserstein Policy Optimization
by: Pfau, David, et al.
Published: (2025)

Gram: Assessing sabotage propensities via automated alignment auditing
by: Lindner, David, et al.
Published: (2026)

Scalable Multi-Objective and Meta Reinforcement Learning via Gradient Estimation
by: Zhang, Zhenshuo, et al.
Published: (2025)

QMGeo: Differentially Private Federated Learning via Stochastic Quantization with Mixed Truncated Geometric Distribution
by: Wang, Zixi, et al.
Published: (2023)

Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient
by: Wang, George, et al.
Published: (2024)

Towards Scalable Meta-Learning of near-optimal Interpretable Models via Synthetic Model Generations
by: Myint, Kyaw Hpone, et al.
Published: (2025)

Do Multilingual LLMs Think In English?
by: Schut, Lisa, et al.
Published: (2025)

Theoretical Analysis of Meta Reinforcement Learning: Generalization Bounds and Convergence Guarantees
by: Wang, Cangqing, et al.
Published: (2024)

Understanding Prompt Tuning and In-Context Learning via Meta-Learning
by: Genewein, Tim, et al.
Published: (2025)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
by: Younesian, Taraneh, et al.
Published: (2023)

MixGCN: Scalable GCN Training by Mixture of Parallelism and Mixture of Accelerators
by: Wan, Cheng, et al.
Published: (2025)

Disentangling the Causes of Plasticity Loss in Neural Networks
by: Lyle, Clare, et al.
Published: (2024)

Meta Hierarchical Reinforcement Learning for Scalable Resource Management in O-RAN
by: Lotfi, Fatemeh, et al.
Published: (2025)

Scalable Decision Focused Learning via Online Trainable Surrogates
by: Signorelli, Gaetano, et al.
Published: (2025)

Scalable On-Policy Reinforcement Learning via Adaptive Batch Scaling
by: Park, Jongchan
Published: (2026)

ScaleBITS: Scalable Bitwidth Search for Hardware-Aligned Mixed-Precision LLMs
by: Li, Xinlin, et al.
Published: (2026)

Generative Modeling of Clinical Time Series via Latent Stochastic Differential Equations
by: Aslanimoghanloo, Muhammad, et al.
Published: (2025)

Differentiable and Stable Long-Range Tracking of Multiple Posterior Modes
by: Younis, Ali, et al.
Published: (2024)

Scalable Property Valuation Models via Graph-based Deep Learning
by: Riveros, Enrique, et al.
Published: (2024)

Imitation Learning from Suboptimal Demonstrations via Meta-Learning An Action Ranker
by: Fan, Jiangdong, et al.
Published: (2024)

Single-Round Scalable Analytic Federated Learning
by: Bacellar, Alan T. L., et al.
Published: (2025)

Scalable Heterogeneous Graph Learning via Heterogeneous-aware Orthogonal Prototype Experts
by: Zhou, Wei, et al.
Published: (2026)

Hierarchical Meta-Reinforcement Learning via Automated Macro-Action Discovery
by: Cho, Minjae, et al.
Published: (2024)

Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version)
by: Ma, Pingchuan, et al.
Published: (2024)

Scalable In-Context Q-Learning
by: Liu, Jinmei, et al.
Published: (2025)

Decision MetaMamba: Enhancing Selective SSM in Offline RL with Heterogeneous Sequence Mixing
by: Kim, Wall, et al.
Published: (2026)

Decision MetaMamba: Enhancing Selective SSM in Offline RL with Heterogeneous Sequence Mixing
by: Kim, Wall, et al.
Published: (2024)

Comprehensive Description of Uncertainty in Measurement for Representation and Propagation with Scalable Precision
by: Darijani, Ali, et al.
Published: (2026)

Efficient Differentiable Causal Discovery via Reliable Super-Structure Learning
by: Ma, Pingchuan, et al.
Published: (2026)

Mixed-Precision Federated Learning via Multi-Precision Over-The-Air Aggregation
by: Yuan, Jinsheng, et al.
Published: (2024)

A Tutorial on Meta-Reinforcement Learning
by: Beck, Jacob, et al.
Published: (2023)

Age and Power Minimization via Meta-Deep Reinforcement Learning in UAV Networks
by: Sarathchandra, Sankani, et al.
Published: (2025)

Integrating Meta-Features with Knowledge Graph Embeddings for Meta-Learning
by: Klironomos, Antonis, et al.
Published: (2026)

Set-based Meta-Interpolation for Few-Task Meta-Learning
by: Lee, Seanie, et al.
Published: (2022)

Meta-Inverse Physics-Informed Neural Networks for High-Dimensional Ordinary Differential Equations
by: Wei, Zhao, et al.
Published: (2026)

Meta-Sel: Efficient Demonstration Selection for In-Context Learning via Supervised Meta-Learning
by: Wang, Xubin, et al.
Published: (2026)