:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Barkley, Brett, Fridovich-Keil, David
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2412.14312
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Forensic Analysis of Synthetic Data in RL: Diagnosing and Solving Algorithmic Failures in Model-Based Policy Optimization
di: Barkley, Brett, et al.
Pubblicazione: (2025)

Scaling Pretrained Representations Enables Label-Free Out-of-Distribution Detection Without Fine-Tuning
di: Barkley, Brett, et al.
Pubblicazione: (2026)

SCOPED: Score-Curvature Out-of-distribution Proximity Evaluator for Diffusion
di: Barkley, Brett, et al.
Pubblicazione: (2025)

Decomposing Control Lyapunov Functions for Efficient Reinforcement Learning
di: Lopez, Antonio, et al.
Pubblicazione: (2024)

Learning to Walk from Three Minutes of Real-World Data with Semi-structured Dynamics Models
di: Levy, Jacob, et al.
Pubblicazione: (2024)

A Recovery Guarantee for Sparse Neural Networks
di: Fridovich-Keil, Sara, et al.
Pubblicazione: (2025)

Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions
di: Remy, Isaac, et al.
Pubblicazione: (2024)

Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty
di: Eisele, Artur, et al.
Pubblicazione: (2026)

Dyna-Style Reinforcement Learning Modeling and Control of Non-linear Dynamics
di: Abdelsalam, Karim, et al.
Pubblicazione: (2025)

No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
di: Wu, Changlong, et al.
Pubblicazione: (2024)

Monotonic Transformation Invariant Multi-task Learning
di: Murthy, Surya, et al.
Pubblicazione: (2025)

Physics-Informed Model and Hybrid Planning for Efficient Dyna-Style Reinforcement Learning
di: Asri, Zakariae El, et al.
Pubblicazione: (2024)

KLIP: localized distribution shift detection via KL-divergence with diffusion priors in Inverse Problems
di: Kheirandish, Alireza, et al.
Pubblicazione: (2026)

Neural Operators for Multi-Task Control and Adaptation
di: Sewell, David, et al.
Pubblicazione: (2026)

Generalized Information Gathering Under Dynamics Uncertainty
di: Palafox, Fernando, et al.
Pubblicazione: (2026)

Symbolic Regression on Sparse and Noisy Data with Gaussian Processes
di: Hsin, Junette, et al.
Pubblicazione: (2023)

When to Trust Your Data: Enhancing Dyna-Style Model-Based Reinforcement Learning With Data Filter
di: Li, Yansong, et al.
Pubblicazione: (2024)

Celo2: Towards Learned Optimization Free Lunch
di: Moudgil, Abhinav, et al.
Pubblicazione: (2026)

A Framework for Finding Local Saddle Points in Two-Player Zero-Sum Black-Box Games
di: Agarwal, Shubhankar, et al.
Pubblicazione: (2025)

Active Inverse Learning in Stackelberg Trajectory Games
di: Ward, William, et al.
Pubblicazione: (2023)

Bayesian Inverse Games with High-Dimensional Multi-Modal Observations
di: Jain, Yash, et al.
Pubblicazione: (2026)

Controllability in preference-conditioned multi-objective reinforcement learning
di: Molins, Pau de las Heras, et al.
Pubblicazione: (2026)

A Flow Matching Algorithm for Many-Shot Adaptation to Unseen Distributions
di: Ingebrand, Tyler, et al.
Pubblicazione: (2026)

Dyna-Style Learning with A Macroscopic Model for Vehicle Platooning in Mixed-Autonomy Traffic
di: Zou, Yichuan, et al.
Pubblicazione: (2024)

Meta-Learning Online Dynamics Model Adaptation in Off-Road Autonomous Driving
di: Levy, Jacob, et al.
Pubblicazione: (2025)

InfoNCE is a Free Lunch for Semantically guided Graph Contrastive Learning
di: Wang, Zixu, et al.
Pubblicazione: (2025)

The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning
di: Goldblum, Micah, et al.
Pubblicazione: (2023)

No Free Lunch: Non-Asymptotic Analysis of Prediction-Powered Inference
di: Mani, Pranav, et al.
Pubblicazione: (2025)

Data-Driven Modeling and Correction of Vehicle Dynamics
di: Ly, Nguyen, et al.
Pubblicazione: (2025)

No Free Lunch: Rethinking Internal Feedback for LLM Reasoning
di: Zhang, Yanzhi, et al.
Pubblicazione: (2025)

Free Lunch for Stabilizing Rectified Flow Inversion
di: Wang, Chenru, et al.
Pubblicazione: (2026)

Accurate, provable and fast polychromatic tomographic reconstruction: A variational inequality approach
di: Lou, Mengqi, et al.
Pubblicazione: (2025)

Integrating Lagrangian Neural Networks into the Dyna Framework for Reinforcement Learning
di: Das, Shreya, et al.
Pubblicazione: (2026)

No-Free-Lunch Theories for Tensor-Network Machine Learning Models
di: Wu, Jing-Chuan, et al.
Pubblicazione: (2024)

StyleShield: Exposing the Fragility of AIGC Detectors through Continuous Controllable Style Transfer
di: Zheng, Guantian
Pubblicazione: (2026)

Auto-Encoding Bayesian Inverse Games
di: Liu, Xinjie, et al.
Pubblicazione: (2024)

FLOSS: Free Lunch in Open-vocabulary Semantic Segmentation
di: Benigmim, Yasser, et al.
Pubblicazione: (2025)

Solving Inverse Problems in Protein Space Using Diffusion-Based Priors
di: Levy, Axel, et al.
Pubblicazione: (2024)

Deceptive Exploration in Multi-armed Bandits
di: Vurankaya, I. Arda, et al.
Pubblicazione: (2025)

Predictive Safety Shield for Dyna-Q Reinforcement Learning
di: Pin, Jin, et al.
Pubblicazione: (2025)