:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Ran, Sheng
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2605.04054
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning Beyond Optimization: Stress-Gated Dynamical Regime Regulation in Autonomous Systems
by: Ran, Sheng
Published: (2026)

On the Identifiability of Regime-Switching Models with Multi-Lag Dependencies
by: Balsells-Rodas, Carles, et al.
Published: (2026)

Regime-Switching Langevin Monte Carlo Algorithms
by: Wang, Xiaoyu, et al.
Published: (2025)

Exploratory Mean-Variance Portfolio Optimization with Regime-Switching Market Dynamics
by: Chen, Yuling Max, et al.
Published: (2025)

Aligning Learning and Endogenous Decision-Making
by: Cristian, Rares, et al.
Published: (2025)

CEBoosting: Online Sparse Identification of Dynamical Systems with Regime Switching by Causation Entropy Boosting
by: Chen, Chuanqi, et al.
Published: (2023)

Dynamic Switch Layers For Unsupervised Learning
by: Li, Haiguang, et al.
Published: (2024)

Deep Switching State Space Model (DS$^3$M) for Nonlinear Time Series Forecasting with Regime Switching
by: Xu, Xiuqin, et al.
Published: (2021)

Auto-FlexSwitch: Efficient Dynamic Model Merging via Learnable Task Vector Compression
by: Gao, Junqi, et al.
Published: (2026)

Dynamic Model Switching for Improved Accuracy in Machine Learning
by: Hasani, Syed Tahir Abbas
Published: (2024)

Improving S&P 500 Volatility Forecasting through Regime-Switching Methods
by: Blake, Ava C., et al.
Published: (2025)

Adaptive Regime-Switching Forecasts with Distribution-Free Uncertainty: Deep Switching State-Space Models Meet Conformal Prediction
by: LU, Echo Diyun, et al.
Published: (2025)

Residual-loss Anomaly Analysis of Physics-Informed Neural Networks: An Inverse Method for Change-point Detection in Nonlinear Dynamical Systems with Regime Switching
by: Bai, Yuhe, et al.
Published: (2026)

Markov Regime-Switching Intelligent Driver Model for Interpretable Car-Following Behavior
by: Zhang, Chengyuan, et al.
Published: (2025)

A Generalized Framework for Multiscale State-Space Modeling with Nested Nonlinear Dynamics: An Application to Bayesian Learning under Switching Regimes
by: Vélez-Cruz, Nayely, et al.
Published: (2024)

Composing Linear Layers from Irreducibles
by: Pence, Travis, et al.
Published: (2025)

FedScalar: Federated Learning with Scalar Communication for Bandwidth-Constrained Networks
by: Rostami, M., et al.
Published: (2024)

Dynamical Regimes of Diffusion Models
by: Biroli, Giulio, et al.
Published: (2024)

Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
by: Luo, Zhiyao, et al.
Published: (2024)

Medical Knowledge Integration into Reinforcement Learning Algorithms for Dynamic Treatment Regimes
by: Yazzourh, Sophia, et al.
Published: (2024)

Evaluating and Learning Optimal Dynamic Treatment Regimes under Truncation by Death
by: Park, Sihyung, et al.
Published: (2025)

On the Identifiability of Switching Dynamical Systems
by: Balsells-Rodas, Carles, et al.
Published: (2023)

Linear Strategic Classification with Endogenous Improvements
by: Shrivastava, Siddharth, et al.
Published: (2026)

Learning Fair Domain Adaptation with Virtual Label Distribution
by: Zhang, Yuguang, et al.
Published: (2026)

Probabilistic Recurrent Intention Switching Model
by: Sheng, Wenyuan, et al.
Published: (2026)

Policy Learning for Optimal Dynamic Treatment Regimes with Observational Data
by: Sakaguchi, Shosei
Published: (2024)

To Switch or Not to Switch? Balanced Policy Switching in Offline Reinforcement Learning
by: Ma, Tao, et al.
Published: (2024)

Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
by: Zaverkin, Viktor, et al.
Published: (2024)

Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations
by: Sverdlov, Yonatan, et al.
Published: (2024)

Near-Equivalent Q-learning Policies for Dynamic Treatment Regimes
by: Yazzourh, Sophia, et al.
Published: (2026)

Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity
by: Li, Jin, et al.
Published: (2021)

Optimizing Digital Therapeutic Interventions: Online Learning under Endogenous Adherence
by: Pulick, Eric, et al.
Published: (2026)

Explainable Learning Rate Regimes for Stochastic Optimization
by: Yang, Zhuang
Published: (2025)

On Agnostic PAC Learning in the Small Error Regime
by: Asilis, Julian, et al.
Published: (2025)

Federated Representation Learning in the Under-Parameterized Regime
by: Liu, Renpu, et al.
Published: (2024)

Dynamical Regimes of Multimodal Diffusion Models
by: Albrychiewicz, Emil, et al.
Published: (2026)

Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes
by: Wang, Di, et al.
Published: (2023)

On Multiple Robustness of Proximal Dynamic Treatment Regimes
by: Gao, Yuanshan, et al.
Published: (2025)

In-Context Learning Under Regime Change
by: Dudley, Carson, et al.
Published: (2026)

HireVAE: An Online and Adaptive Factor Model Based on Hierarchical and Regime-Switch VAE
by: Wei, Zikai, et al.
Published: (2023)