Hidden Markov models: inverse filtering, belief estimation and privacy protection
DOI10.1007/s11424-021-1247-1zbMath1480.93425OpenAlexW3209716322MaRDI QIDQ2070019
Cristian R. Rojas, Inês Lourenço, B. Wahlberg, Robert Mattila, Xiao-ming Hu
Publication date: 21 January 2022
Published in: Journal of Systems Science and Complexity (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11424-021-1247-1
hidden Markov modelsinverse filteringbelief estimationcounter-adversarial systemsinverse decision making
Decision theory (91B06) Filtering in stochastic control theory (93E11) Markov processes: estimation; hidden Markov models (62M05) Portfolio theory (91G10)
Related Items (2)
Cites Work
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- A spectral algorithm for learning hidden Markov models
- Inverse optimization for linearly constrained convex separable programming problems
- Inverse conic programming with applications
- Discrete-time inverse linear quadratic optimal control over finite time-horizon under noisy output measurements
- Continuous-time inverse quadratic optimal control problem
- Inverse optimal control for discrete-time finite-horizon linear quadratic regulators
- Inference in hidden Markov models.
- Partially Observed Markov Decision Processes
- Inverse Optimization
- Markov Chains
- Dynamic portfolio optimization across hidden market regimes
- Inverse Filtering for Hidden Markov Models With Applications to Counter-Adversarial Autonomous Systems
- How to Calibrate Your Adversary's Capabilities? Inverse Filtering for Counter-Autonomous Systems
- Markowitz's Mean-Variance Portfolio Selection With Regime Switching: From Discrete-Time Models to Their Continuous-Time Limits
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