Papers by Jen-Tzung Chien
AVAST: Attentive Variational State Tracker in a Reinforced Navigator (2022.aacl-main)
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| Challenge: | Recent advances in reinforcement learning have been proposed to deal with robotic navigation problems, especially vision-and-language navigation task. |
| Approach: | They propose a method to approximate belief state distribution for the construction of a reinforced navigator by using a variational approach to approximate the unseen environment. |
| Outcome: | The proposed method improves generalization to the unseen environment which is barely achieved by traditional deterministic state tracker. |
Deep Bayesian Learning and Understanding (C18-3)
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| Challenge: | COLING 2018 is a conference for researchers and practitioners working on machine learning and deep learning. |
| Approach: | a tutorial on machine learning and deep learning will be presented at COLING 2018 . the tutorial will focus on statistical models, deep neural networks, sequential learning and natural language understanding . |
| Outcome: | This tutorial will present the latest advances in deep Bayesian and sequential learning at COLING 2018 . |
Deep Bayesian Natural Language Processing (P19-4)
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| Challenge: | Introduction to deep Bayesian learning for natural language addresses the fundamentals of statistical models and neural networks. |
| Approach: | This tutorial addresses the advances in deep Bayesian learning for natural language . it focuses on advanced Bayessian models and deep models . authors present case studies and domain applications to tackle different issues . |
| Outcome: | This tutorial focuses on advanced Bayesian models and deep models for natural language . case studies and domain applications are presented to tackle different issues in deep Bayessian processing, learning and understanding. |