Learning switched non-linear dynamical systems from a single trajectory

arXiv:2607.23502 · stat.ML, cs.LG, math.ST · Submitted 2026-07-26 · Read on arXiv

Sunny G. W. Wang, Hemant Tyagi

stat.ML, cs.LG, math.ST

Submitted: 2026-07-26

Comments: 56 pages, 2 figures

Code: https://github.com/sunnywang93/switchnds

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Fixed Point — 5× in this paper · explained in 2 episodes
• System Identification — 4× in this paper · explained in 3 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Hybrid System — 2× in this paper · explained in 2 episodes
• Localization — 2× in this paper · explained in 2 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Formal Methods — 1× in this paper · explained in 3 episodes
• IEEE Conference on Decision and Control — 1× in this paper
• Phase Transition — 1× in this paper · explained in 3 episodes
• Regret — 1× in this paper · explained in 4 episodes
• Regret Bound — 1× in this paper · explained in 2 episodes
• Regret Bounds — 1× in this paper · explained in 2 episodes
• Sample Complexity — 1× in this paper · explained in 20 episodes

Sources

• Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
• Strong Consistency and Rate of Convergence of Switched Least Squares System Identification for Autonomous Markov Jump Linear Systems
• Physics-informed learning under mixing: How physical knowledge speeds up learning

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