How are stochastic processes used in machine learning (e.g., Hidden Markov Models)?

Jul 30, 2018 ... Correlated stochastic process (colored noises) with f − k power spectrum (⁠ 0 < k ≤ 3 ⁠) is characterized by intermediate permutation entropy ... Wu is with School of Mathematics and Informational Science,. Yantai ... Proposition 2: If a stochastic process is locally strongly uni- formly ... Mar 22, 2011 ... ... stochastic process is present in commodity prices. In addition, we build a dynamic stochastic general equilibrium model with informational ... ... Informational Risks, Peking Univ. Ser. Math. 5 ... Jeanblanc, No-arbitrage under additional information for thin semimartingale models, Stochastic Process. Jul 6, 2021 ... Asymmetric information may stem from, e.g., the observation of different stochastic processes or partial knowledge of the structure of the game ... the entropy rate of a stochastic process (message or sequence is seen as a succession of events). (The "rate of self-information" can also be defined for a ... ... stochastic processes or theoretical models. With the development of transfer ... In the bivariate case, information flow from process J to process I is ... This paper develops a subordinated stochastic process model for asset prices, where the directing process is identified as information. Motivated by recent. Mar 15, 2023 ... Abstract. Some mathematical models of informational signals and methods of the diagnostic system construction is considered. Different type of ... The analysis of the stochastic process reveals the properties of the informational cascade and the informational avalanche. 4.1. Optimal trading strategy.