Driver State Modeling Through Latent Variable State Space Framework in the Wild

Latent-Variable Modeling of String Transductions with Finite-State Methods

String-to-string transduction is a central problem in computational linguistics and natural language processing. It occurs in tasks as diverse as name transliteration, spelling correction, pronunciation modeling and inflectional morphology. We present a conditional loglinear model for string-to-string transduction, which employs overlapping features over latent alignment sequences, and which le...

State-Space Reduction through Preference Modeling

Automated planning for numerous co-existing agents, with uncertainty caused by various levels of their predictability, observability and autonomy, is a complex task. One of the most significant issues is related to explosion of the state space. This paper presents a formal framework which can be used to model such systems and proposes the use of formally-modeled agents’ preferences as a way of ...

State Space Techniques in Structural Equation Modeling Transformation of latent variables in and out of latent variable models

State-level variable modeling for

In HMM-based pattern recognition, the structure of the HMM is often predetermined according to some prior knowledge. In the recognition process, we usually make our judgment based on the maximum likelihood of the HMM, without considering the time-varying property of state-level variables, which unfortunately may lead to incorrect results. In this paper, we analyze the property of state-level va...

Advanced Fuel Cell System Control through State Space Modeling

Maintaining a fuel cell system in correct operating conditions when subjected to fast load changes requires good system control. In order to design such a controller, a simple PEFC system model describing all the important system dynamics and cross couplings is required. The simple model shown here describes the fuel cell auxiliary systems in a state space approach, linking user input to fuel c...