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Publications

Journal Publications

  1. ” New Concept of Multiple Neural Networks Structure Using Convex Combination”, Yu Wang, Yue Deng, Yilin Shen, Hongxia Jin, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020 [Text in pdf]

 

Conference Publications

Deep Reinforcement Learning

  1. “An Interactive Adversarial Reward Learning-based Spoken Language Understanding System”, Yu Wang, Yilin Shen, Hongxia Jin, in the Proceedings of  the 21th InterSpeech (InterSpeech), 2020 [Text in pdf]
  2. “A Deep Reinforcement Learning based Multi-step Coarse to Fine Question Answering (MSCQA) System”, Yu Wang, Hongxia Jin, in the Proceedings of the 33th AAAI Conference on Artificial Intelligence (AAAI), 2019 [Text in pdf]
  3. “New Concept of Deep Reinforcement Learning based Augmented General Tagging System”, Yu Wang, A Patel, H Jin, in the Proceedings of the 27th International Conference on Computational Linguistics (COLING), 2018  [Text in pdf]
  4. “A Deep Reinforcement Learning Based Multimodal Coaching Model (DCM) for Slot Filling in Spoken Language Understanding (SLU)”, Yu Wang, A Patel, Y Shen, H Jin, in the Proceeding of InterSpeech, 2018 [Text in pdf]
  5. A Boosting-based Deep Neural Networks Algorithm for Reinforcement Learning”, Yu Wang, Hongxia Jin,  2018 American Control Conference (ACC), Invited as the Machine Learning Session Chair [Text in pdf]
  6. “Fast reinforcement learning using multiple models”, Narendra, Kumpati S., Yu Wang, Mukhopadhyay S., 2016 Control and Decision Conference (CDC), Invited as the Learning Session Chair [Text in pdf]
  7. “Improving the Speed of Response of Learning Algorithms using Multiple Models”, Narendra, Kumpati S., Mukhopadhyay S., Yu Wang, 17th Yale Workshop on Adaptive and Learning Systems, 2015 [Text in pdf]
  8. “Simulation Studies of Feed-forward Learning Schemes with Multiple Models”, Narendra, Kumpati S., Yu Wang, Yale technical report 1603.

Natural Language Understanding, Question Answering, Dialogue State Tracking

  1. “A BI-Model Approach for Handling Unknown Slot Values in Dialogue State Tracking”, Yu Wang, Yilin Shen, Hongxia Jin, in the Proceedings of  the 45th International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020 [Text in pdf]
  2. “An Interactive Adversarial Reward Learning-based Spoken Language Understanding System”, Yu Wang, Yilin Shen, Hongxia Jin, in the Proceedings of  the 21th InterSpeech, 2020 [Text in pdf]
  3. “An Interpretable Multimodal Visual Question Answering System using Attention-based Weighted Contextual Features”, Yu Wang, Yilin Shen, Hongxia Jin, in the Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2020 [Text in pdf]
  4. “A Deep Reinforcement Learning based Multi-step Coarse to Fine Question Answering (MSCQA) System”, Yu Wang, Hongxia Jin, in the Proceedings of the 33th AAAI Conference on Artificial Intelligence (AAAI), 2019 [Text in pdf]
  5. “Sliqa-i: Towards cold-start development of end-to-end spoken language interface for question answering”, Yilin Shen, Yu Wang, Abhishek Patel, Hongxia Jin, in the Proceedings of  the 44th International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019 [Text in pdf]
  6. ” New Concept of Deep Reinforcement Learning based Augmented General Tagging System”, Yu Wang, A Patel, H Jin, in the Proceedings of the 27th International Conference on Computational Linguistics (COLING), 2018  [Text in pdf]
  7. “A Neural Transition-based Model for Nested Mention Recognition”, Bailin Wang, Wei Lu, Yu Wang, Hongxia Jin, 2018 Conference on Empirical Methods in Natural Language Processing   (EMNLP) [Text in pdf]
  8. “User Information Augmented Semantic Frame Parsing Using Progressive Neural Networks”, Yilin Shen, Xiangyu Zeng, Yu Wang, Hongxia Jin, in the Proceeding of InterSpeech, 2018 [Text in pdf]
  9. “A Deep Reinforcement Learning Based Multimodal Coaching Model (DCM) for Slot Filling in Spoken Language Understanding (SLU)”, Yu Wang, A Patel, Y Shen, H Jin, in the Proceeding of the 19th InterSpeech, 2018 [Text in pdf]
  10. A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling, Yu Wang, Yilin Shen and Hongxia Jin, in the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2018 (Acceptance rate: 29.4%) [Text in pdf]
  11. “NLP Query Classification using Deep Learning- An implementation using Tensorflow”, Yu Wang, Yale Machine Learning Tutorial Series(link)

Deep Neural Networks and Deep Learning

  1. ” New Concept of Multiple Neural Networks Structure Using Convex Combination”, Yu Wang, Yue Deng, Yilin Shen, Hongxia Jin, IEEE Transactions on Neural Networks and Learning Systems (Journal), 2020 [Text in pdf]
  2. “User Information Augmented Semantic Frame Parsing Using Progressive Neural Networks”, Yilin Shen, Xiangyu Zeng, Yu Wang, Hongxia Jin, in the Proceeding of InterSpeech, 2018 [Text in pdf]
  3. “A New Concept using LSTM Neural Networks for Dynamic System”, Yu Wang, 2017 ACC.[Text in pdf]
  4. “A Supervised Learning-based fuzzy controller for a non-linear vehicle system using Neural Network Identification”, Yu Wang and Xiaoxi Zhu, 2016 American Control Conference (ACC), Boston, Invited as the Neural Network & Fuzzy Control Session Chair [Text in pdf]

Multiple Models Adaptive Learning and Control

  1. “Improving the Speed of Response of Learning Algorithms using Multiple Models”, Narendra, Kumpati S., Mukhopadhyay S., Yu Wang, 17th Yale Workshop on Adaptive and Learning Systems, 2015[Text in pdf]
  2. “Simulation Studies of Feed-forward Learning Schemes with Multiple Models”, Narendra, Kumpati S., Yu Wang, Yale technical report 1603.
  3. “Extension of Second Level Adaptation using Multiple Models to SISO System”,  Narendra, Kumpati S., Yu Wang, and Wei Chen. American Control Conference (ACC), 2015. IEEE, 2015.[Text in pdf]
  4. “Stability, robustness, and performance issues in second level adaptation.” Narendra, Kumpati S., Yu Wang, and Wei Chen, American Control Conference (ACC), 2014. IEEE, 2014. [Text in pdf]
  5. “The Rationale for Second Level Adaptation”, Narendra, Kumpati S., Yu Wang, and Wei Chen, 16th Yale Workshop on Adaptive and Learning Systems, 2013 [Text in pdf]

Fuzzy Logic, Unmanned Vehicles, Autonomous Driving/Parking:

  1. “A Supervised Learning-based fuzzy controller for a non-linear vehicle system using Neural Network Identification”, Yu Wang and Xiaoxi Zhu, 2016 American Control Conference (ACC), Boston, Invited as the Neural Network & Fuzzy Control Session Chair [Text in pdf]
  2. “A robust design of Hybrid Fuzzy Controller with Fuzzy Decision Tree for autonomous intelligent parking system.”, Yu Wang and Xiaoxi Zhu, 2014 American Control Conference (ACC). IEEE, 2014.[Text in pdf]
  3. “Hybrid Fuzzy Logic Controller for optimized autonomous parking.”, Yu Wang and Xiaoxi Zhu, 2013 American Control Conference (ACC). IEEE, 2013.[Text in pdf]
  4. “Design and implementation of an integrated multi-functional autonomous parking system with Fuzzy logic controller.”, Yu Wang and Xiaoxi Zhu,  2012 American Control Conference (ACC), Montreal, Canada. 2012.[Text in pdf]

News!

2020/11 My Journal paper on TNNLS (Impact Factor: 11.683) "A New Concept of Multiple Neural Networks Structure Using Convex Combination" is finally published!

2020/09 My paper on spoken language understanding "An Interactive Adversarial Reward Learning-based Spoken Language Understanding System" is presented at InterSpeech 2020, virtually on-line due to Covid-19.

2020/05 My paper on Multi-modal VQA "An Interpretable Multimodal Visual Question Answering System using Attention-based Weighted Contextual Features" is presented at AAMAS 2020, virtually on-line due to Covid-19.

2020/05 My paper on Dialogue State Tracking "A Bi-Model Approach for Handling Unknown Slot Values in Dialogue State Tracking" is presented at ICASSP 2020, virtually on-line due to Covid-19.

2019/06 Our paper "Sliqa-i: Towards cold-start development of end-to-end spoken language interface for question answering" is presented ICASSP 2019

2019/02 My paper "A Deep Reinforcement Learning based Multi-Step Coarse to Fine Question Answering (MSCQA) System" is presented AAAI 2019, Hawaii! Aloha!!

2018/11 My paper "An interpretable (Conversational) VQA model using Attention based Weighted Contextual Features" is accepted to NIPS 2018, workshop on Conversational AI

2018/11 Our Paper "A neural transition-based model for nested mention recognition" is presented at EMNLP 2018.

2018/06 My paper "A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling" is presented at NAACL 2018.

2018/06 I am invited as the Machine Learning Area Chair at 2018 American Control Conference (ACC 2018). Thanks to our conference organizers!

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