Rodney Nielsen

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Recently proposed classification algorithms give estimates or worst-case bounds for the probability of misclassification [Lanckriet et al., 2002][L. Breiman, 2001]. These accuracy estimates are for all future predictions, even though some predictions are more likely to be correct than others. This paper introduces Probabilistic Random Forests (PRF), which(More)
Truly effective and practical educational systems will only be achievable when they have the ability to fully recognize deep relationships between a learner's interpretation of a subject and the desired conceptual understanding. In this paper, we take important steps in this direction by introducing a new representation of sentences – Minimal Meaningful(More)
In this study, we applied a deep LSTM structure to classify dialogue acts (DAs) in open-domain conversations. We found that the word embeddings parameters, dropout regularization, decay rate and number of layers are the parameters that have the largest effect on the final system accuracy. Using the findings of these experiments, we trained a deep LSTM(More)
Recently proposed classification algorithms give estimates or worst-case bounds for the probability of misclassification [Lanckriet et al., 2002][L. Breiman, 2001]. These accuracy estimates are for all future predictions, even though some predictions are more likely to be correct than others. This paper introduces Probabilistic Random Forests (PRF), which(More)
In this paper, we describe a dialogue system framework for a companionable robot, which aims to guide patients towards health behavior changes via natural language analysis and generation. The framework involves three broad stages, rapport building and health topic identification , assess patient's opinion of change, and designing plan and closing session.(More)
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