:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Steier, Joshua
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2603.01309
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

When Does Margin Clamping Affect Training Variance? Dataset-Dependent Effects in Contrastive Forward-Forward Learning
by: Steier, Joshua
Published: (2026)

Information Routing in Atomistic Foundation Models: How Task Alignment and Equivariance Shape Linear Disentanglement
by: Steier, Joshua
Published: (2026)

The Sample Complexity of Replicable Realizable PAC Learning
by: Larsen, Kasper Green, et al.
Published: (2026)

HyPAC: Cost-Efficient LLMs-Human Hybrid Annotation with PAC Error Guarantees
by: Zeng, Hao, et al.
Published: (2026)

Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation
by: Sucker, Michael, et al.
Published: (2024)

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting
by: Hanneke, Steve, et al.
Published: (2026)

PAC-Bayesian Generalization Guarantees for Fairness on Stochastic and Deterministic Classifiers
by: Bastian, Julien, et al.
Published: (2026)

Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory
by: Zhang, Zhi, et al.
Published: (2024)

PAC Apprenticeship Learning with Bayesian Active Inverse Reinforcement Learning
by: Bajgar, Ondrej, et al.
Published: (2025)

PAC-Bayesian Reinforcement Learning Trains Generalizable Policies
by: Zitouni, Abdelkrim, et al.
Published: (2025)

Data-Driven Reachability Analysis via Diffusion Models with PAC Guarantees
by: Huang, Yanliang, et al.
Published: (2026)

On the Complexity of Offline Reinforcement Learning with $Q^\star$-Approximation and Partial Coverage
by: Liu, Haolin, et al.
Published: (2026)

Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
by: Zhou, Sijia, et al.
Published: (2025)

A Variance-Based Analysis of Sample Complexity for Grid Coverage
by: Yuhuan, Lyu
Published: (2025)

A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees
by: Kitamura, Toshinori, et al.
Published: (2024)

Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data
by: Zou, Xin, et al.
Published: (2024)

Conformal Prediction for Indoor Positioning with Correctness Coverage Guarantees
by: Zhou, Zhiyi, et al.
Published: (2025)

Probabilistic Conformal Coverage Guarantees in Small-Data Settings
by: Zwart, Petrus H.
Published: (2025)

Guaranteed Coverage Prediction Intervals with Gaussian Process Regression
by: Papadopoulos, Harris
Published: (2023)

Settling the Sample Complexity of Online Reinforcement Learning
by: Zhang, Zihan, et al.
Published: (2023)

Achieving PAC Guarantees in Mechanism Design through Multi-Armed Bandits
by: Osogami, Takayuki, et al.
Published: (2024)

Reinforcement Learning for Control with Probabilistic Stability Guarantee: A Finite-Sample Approach
by: Han, Minghao, et al.
Published: (2026)

Variational Inference with Coverage Guarantees in Simulation-Based Inference
by: Patel, Yash, et al.
Published: (2023)

Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees
by: Jaber, Edgar, et al.
Published: (2024)

On the Computability of Robust PAC Learning
by: Gourdeau, Pascale, et al.
Published: (2024)

Efficient Optimal PAC Learning
by: Høgsgaard, Mikael Møller
Published: (2025)

Symmetries in PAC-Bayesian Learning
by: Beck, Armin, et al.
Published: (2025)

On the Computability of Multiclass PAC Learning
by: Gourdeau, Pascale, et al.
Published: (2025)

Tail-Risk-Safe Monte Carlo Tree Search under PAC-Level Guarantees
by: Zhang, Zuyuan, et al.
Published: (2025)

On The Sample Complexity Bounds In Bilevel Reinforcement Learning
by: Gaur, Mudit, et al.
Published: (2025)

Optimizing Coverage and Difficulty in Reinforcement Learning for Quiz Composition
by: Silva, Ricardo Pedro Querido Andrade, et al.
Published: (2026)

Generalization Bounds via Meta-Learned Model Representations: PAC-Bayes and Sample Compression Hypernetworks
by: Leblanc, Benjamin, et al.
Published: (2024)

Error Exponent in Agnostic PAC Learning
by: Hendel, Adi, et al.
Published: (2024)

Learning via Surrogate PAC-Bayes
by: Picard-Weibel, Antoine, et al.
Published: (2024)

CONTINA: Confidence Interval for Traffic Demand Prediction with Coverage Guarantee
by: Yang, Chao, et al.
Published: (2025)

Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning
by: Mollaali, Amirhossein, et al.
Published: (2025)

PAC Learning with Improvements
by: Attias, Idan, et al.
Published: (2025)

Sample Complexity Analysis for Constrained Bilevel Reinforcement Learning
by: Saxena, Naman, et al.
Published: (2026)

Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning
by: Liu, Junyan, et al.
Published: (2024)

Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling
by: Aouali, Imad, et al.
Published: (2024)