PhD Thesis Researches

Researchers PHD Thesis Titles Keywords Period   Xiao FU Study on Symbolic Singing Annotation and Monophonic Music Generation Using Deep Neural Networks Symbolic singing annotation, Monophonic music generation, Automatic singing label calibration, Deep neural networks, Convolutional neural networks, Deep learning, Transfer learning, Transformer, Generative adversarial network, Monte Carlo tree search 2019.4～2024.6 Hangy DENG Study on Personalized Recommendations Based on Behavioral Sequence Modeling Using Deep Neural Networks Personalized recommendation systems, Behavioral sequence modeling, Subsequence extraction, Subsequence modeling, Machine learning, Deep learning, Deep neural networks, Graph neural network, Multilay perceptron, Convolutional neural network, Self-attention, Transformer 2019.4～2024.5 Huilin ZHU Study on Nonlinear Regression with Missing Values Based on Hybrid Models Using Quasi-Linear Kernel Nonlinear regression, Missing value prediction, Hybrid models, Support vector regression, Quasi-linear kernel, Multi-local linear model, Piecewise linear model, Denoising autoencoder, Winner-take-all autoencoder, Mutilayer gated linear network, Affinity propagation clustering, Adversarial training process 2018.9～2022.11 Jiaying WU Study on Few-Shot Image Classification Based on Class Distribution Estimation Using Maximum A Posteriori Few-shot learning, Image classification, Deep learning, Feature hallucination, Gaussian distribution, Maximum a Posteriori, Power transformation, Visual representation, Semantic representation, Representation bias, Triplet network, Constrative learning, Redefining prior feature space 2019.9～2022.9 Xin YUAN Study on Deep Transfer Learning Methods for the Predictions of Protein Functions Protein function prediction, GO annotation prediction, Protein subcellular localization prediction, Protein-protein interaction prediction, Protein complex detection, Deep convolutional neural network, Multi-head multi-end model, Deep learning, Transfer learning 2017.9～2022.6 Yanni REN Study on Semi-Supervised Classification Based on Laplacian Kernel Machines Using Quasi-Linear Kernel Nonlinear classification, Semi-Supervised classification, Kernel machines, Laplacian support vector machine, Quasi-linear kernel, Multi-local linear model, Piecewise linear model, Pseudo-labeling approach, Label-guided autoencoder, Winner-take-all autoencoder, Gated linear network, Deep neural network, Contrastive learning 2018.9～2022.2 Peifeng LIANG Study on SVM Classifiers for Imbalanced Data Classification Using Quasi-Linear Kernel Nonlinear classification, Imbalanced data classification, One class classification, Support vector machine, Quasi-linear kernel, Piecewise linear modeling, Local off-sets, Synthetic minority oversampling, Winner-take-all autoencoder, Gated linear network, Deep neural network 2013.4～2021.1 Weite LI Study on Quasi-Linear Kernel Composition for Support Vector Machines using Supervised, Unsupervised and Transfer Learning Nonlinear classification, Support vector machine, Kernel composition and learning, Supervised learning, Unsupervised learning, Transfer learning, Manifold learning, Deep neural networks, Local linear modeling, Piecewise linear modeling, Deep quasi-linear kernel 2016.4～2019.3 Bo ZHOU Study on SVMs with Quasi-Linear Kernel for Imbalanced Classification and Semi-supervised Classification Nonlinear classification, Imbalanced learning, Semi-supervised learning, Oversampling, SMOTE, Density-based clustering, Support vector machine, Laplacian SVM, Quasi-linear kernel, Data-dependent kernel, local linear partition 2009.9～2018.9 Sutrisno IMAM Study on Self-Organizing Quasi-Linear ARX RBFN Model and Its Application to Adaptive Control of Nonlinear Systems Nonlinear system identification, Controller design, Switching control, Quasi-linear ARX model, Self-Organization, Radial basis networks, Predictor with bounded prediction error 2011.9～2017.3 Mohammad A. JAMI'IN Study on Lyapunov-based Identification and Control of Nonlinear Systems Using Quasi-linear ARX Neural Network Model Nonlinear system identification, Controller design, Switching control, Lyapunov stability theory, Quasi-linear ARX model, Neural networks, Wind energy conversion system, Maximum power tracking control 2012.4～2016.3 Yu CHNEG Study on Identification of Nonlinear Systems Using Quasi-ARX Models Nonlinear system identification, Linear-in-parameter, Quasi-ARX Modeling, Neural networks, Wavelet networks, SVR, Genetic algorithm, Multi-objective optimization, Clustering 2009.9～2012.9 Lan WANG Study on Adaptive Control of Nonlinear Dynamical Systems Based on Quasi-ARX Models Nonlinear system, Quasi-ARX Model, Neural network, Wavelet network, Neuro-fuzzy network, RBF network, Adaptive control, Switching mechanism, Stability, Accuracy, SVR, Model predictive control, Nonlinear PCA 2008.9～2011.9 Benhui CHEN Study on the Predictions of Protein Structure and Function Using Multi-SVM and Hybrid EDA Protein structure prediction, Lattice HP model, Estimation distribution algorithm (EDA), Adaptive Niching EDA, Protein function prediction, Support vector machines (SVM), Multi-SVM system, Multi-label classification, Hierarchical multi-label classification 2008.4～2011.3 Boyang LI Study on Multi-SVM Systems and Their Application to Pattern Recognition Support vector machines, Kernel based methods, Pattern recognition, Fast training, Feature selection, Fuzzy decision boundary, Multi-SVM system, Modular SVR network, Class imbalance 2006.9～2010.9 笹川 隆史 複合型学習と脳の機能局在性を考慮したニューラルネットワークに関する研究 Neural network, Self-organizing map, Function localization, Brainlike model, Supervised learning, Unsupervised learning, Reinforcement learning, Modular network, Dynamical overlapping 2003.4～2008.3