Tingting Zhao

Orcid: 0000-0001-5915-503X

Affiliations:
  • Tianjin University of Science and Technology, College of Artificial Intelligence, China
  • Tokyo Institute of Technology, Japan (former)


According to our database1, Tingting Zhao authored at least 32 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Teaching practice of wind turbine practical training based on virtual teaching platform.
Comput. Appl. Eng. Educ., March, 2024

Learning explainable task-relevant state representation for model-free deep reinforcement learning.
Neural Networks, 2024

Hybrid Deep Generative and Sequential Learning Approach for Stock Market Prediction.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024

AugSBertChat: User Feedback-Enhanced QA with Sentence-RoBERTa.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024

PS-DeiT: A Part-Selection Based DeiT for Fine-Grained Classification.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024

LDCM-MVIT: A Lightweight Depth Completion Model Based on MViT.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024

2023
Learning Intention-Aware Policies in Deep Reinforcement Learning.
Neural Comput., October, 2023

Representation learning for continuous action spaces is beneficial for efficient policy learning.
Neural Networks, February, 2023

A multi-scenario text generation method based on meta reinforcement learning.
Pattern Recognit. Lett., January, 2023

2022
Bidirectional Multi-channel Semantic Interaction Model of Labels and Texts for Text Classification.
Proceedings of the Natural Language Processing and Chinese Computing, 2022

Exploiting Dynamic and Fine-grained Semantic Scope for Extreme Multi-label Text Classification.
Proceedings of the Natural Language Processing and Chinese Computing, 2022

Exploring Topic Supervision with BERT for Text Matching.
Proceedings of the International Joint Conference on Neural Networks, 2022

2021
A model-based reinforcement learning method based on conditional generative adversarial networks.
Pattern Recognit. Lett., 2021

End-to-End Pre-trained Dialogue System for Automatic Diagnosis.
Proceedings of the CCKS 2021 - Evaluation Track, 2021

2019
Mixture variational autoencoders.
Pattern Recognit. Lett., 2019

Web-based SBLR method of multimedia tools for computer-aided drawing.
Multim. Tools Appl., 2019

Green Internet of Vehicles: Architecture, Enabling Technologies, and Applications.
IEEE Access, 2019

Latent Gaussian-Multinomial Generative Model for Annotated Data.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

2018
Face recognition using weber local circle gradient pattern method.
Multim. Tools Appl., 2018

Stroke-based stylization by learning sequential drawing examples.
J. Vis. Commun. Image Represent., 2018

Face Recognition based on Weber Symmetrical Local Graph Structure.
KSII Trans. Internet Inf. Syst., 2018

2017
Ferrography Wear Particles Image Recognition Based on Extreme Learning Machine.
J. Electr. Comput. Eng., 2017

Dynamic Task Scheduling Via Policy Iteration Scheduling Approach for Cloud Computing.
KSII Trans. Internet Inf. Syst., 2017

2016
Trial and Error: Using Previous Experiences as Simulation Models in Humanoid Motor Learning.
IEEE Robotics Autom. Mag., 2016

An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions.
Neural Comput., 2016

2015
Stroke-Based Stylization Learning and Rendering with Inverse Reinforcement Learning.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Regularized Policy Gradients: Direct Variance Reduction in Policy Gradient Estimation.
Proceedings of The 7th Asian Conference on Machine Learning, 2015

2014
Model-based policy gradients with parameter-based exploration by least-squares conditional density estimation.
Neural Networks, 2014

Efficient Reuse of Previous Experiences to Improve Policies in Real Environment.
CoRR, 2014

Efficient reuse of previous experiences in humanoid motor learning.
Proceedings of the 14th IEEE-RAS International Conference on Humanoid Robots, 2014

2013
Efficient Sample Reuse in Policy Gradients with Parameter-Based Exploration.
Neural Comput., 2013

2012
Analysis and improvement of policy gradient estimation.
Neural Networks, 2012


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