Jung-Chun Chen

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This paper presents a new recursive Bayesian linear regression (RBLR) algorithm for adaptive pattern classification. This algorithm performs machine learning in nonstationary environments. A classification model is adopted in model training. The initial model parameters are estimated by maximizing the likelihood function of training data. To activate the(More)
This paper presents a new Bayesian regression and learning algorithm for adaptive pattern classification. Our aim is to continuously update regression parameters to meet nonstationary environments for real-world applications. Here, a kernel regression model is used to represent two-class data. The initial regression parameters are estimated by maximizing(More)
This paper presents a Bayesian learning approach to large margin classifier for hidden Markov model (HMM) based speech recognition. We build the Bayesian large margin HMMs (BLM-HMMs) and improve the model generalization for handling unknown test environments. Using BLM-HMMs, the variational Bayesian HMM parameters are estimated by maximizing lower bound of(More)
Population aging is an important issue in Taiwan. The percentage of elderly members of the population has been growing quickly during recent years. The requirements of long-term care for chronic and functionally impaired patients are rapidly increasing. Beside medical treatment, the needs of long-term care facilities are also continuously increasing. Among(More)
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