Advanced topics in Machine Learning K31

Master class in Computer Science 31st school year - (Máy học nâng cao - Cao học K31)

Decision Tree - Cây quyết định

• C. Nunes, H. Langet, M. De Craene, O. Camara, B. Bijnens and A. Jonsson, "Decision Tree Learning for Uncertain Clinical Measurements," in IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 9, pp. 3199-3211, 1 Sept. 2021, doi: 10.1109/TKDE.2020.2967378.
• J. Liang, Z. Qin, L. Xue, X. Lin and X. Shen, "Efficient and Privacy-Preserving Decision Tree Classification for Health Monitoring Systems," in IEEE Internet of Things Journal, vol. 8, no. 16, pp. 12528-12539, 15 Aug.15, 2021, doi: 10.1109/JIOT.2021.3066307.
• Y. Dhebar and K. Deb, "Interpretable Rule Discovery Through Bilevel Optimization of Split-Rules of Nonlinear Decision Trees for Classification Problems," in IEEE Transactions on Cybernetics, vol. 51, no. 11, pp. 5573-5584, Nov. 2021, doi: 10.1109/TCYB.2020.3033003.

Neural Network

• Z. Chen, L. Deng, B. Wang, G. Li and Y. Xie, "A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 1, pp. 13-31, 1 Jan. 2022, doi: 10.1109/TPAMI.2020.3010201.
• L. Xu, X. Cao, J. Yao and Z. Yan, "Orthogonal Super Greedy Learning for Sparse Feedforward Neural Networks," in IEEE Transactions on Network Science and Engineering, vol. 9, no. 1, pp. 161-170, 1 Jan.-Feb. 2022, doi: 10.1109/TNSE.2020.3033418.
• Lee S, Song BC. Knowledge Transfer via Decomposing Essential Information in Convolutional Neural Networks. IEEE Trans Neural Netw Learn Syst. 2022 Jan;33(1):366-377. doi: 10.1109/TNNLS.2020.3027837. Epub 2022 Jan 5. PMID: 33048771.

Boosting/ AdaBoost

• L. Wang, S. Li, S. Wang, D. Kong and B. Yin, "Hardness-Aware Dictionary Learning: Boosting Dictionary for Recognition," in IEEE Transactions on Multimedia, vol. 23, pp. 2857-2867, 2021, doi: 10.1109/TMM.2020.3017916.
• Y. Xu, Z. Yu, W. Cao, C. L. P. Chen and J. You, "Adaptive Classifier Ensemble Method Based on Spatial Perception for High-Dimensional Data Classification," in IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 7, pp. 2847-2862, 1 July 2021, doi: 10.1109/TKDE.2019.2961076.
• Z. Zhu, Z. Wang, D. Li, Y. Zhu and W. Du, "Geometric Structural Ensemble Learning for Imbalanced Problems," in IEEE Transactions on Cybernetics, vol. 50, no. 4, pp. 1617-1629, April 2020, doi: 10.1109/TCYB.2018.2877663.

Genetic Algorithm

• Y. Bi, B. Xue and M. Zhang, "A Divide-and-Conquer Genetic Programming Algorithm With Ensembles for Image Classification," in IEEE Transactions on Evolutionary Computation, vol. 25, no. 6, pp. 1148-1162, Dec. 2021, doi: 10.1109/TEVC.2021.3082112.
• Q. Fan, S. Wu, X. Zhou, L. Li and Z. Wang, "A Genetic Algorithm Based on Auxiliary-Individual-Directed Crossover for Internet-of-Things Applications," in IEEE Internet of Things Journal, vol. 8, no. 7, pp. 5518-5530, 1 April1, 2021, doi: 10.1109/JIOT.2020.3031922.
• J. Tang, Y. Yang, W. Hao, F. Liu and Y. Wang, "A Data-Driven Timetable Optimization of Urban Bus Line Based on Multi-Objective Genetic Algorithm," in IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 4, pp. 2417-2429, April 2021, doi: 10.1109/TITS.2020.3025031.

Reinforcement Learning

• Cao Z, Kwon M, Sadigh D. Transfer reinforcement learning across homotopy classes. IEEE Robotics and Automation Letters. 2021 Feb 3;6(2):2706-13.
• C. Sun, W. Liu and L. Dong, "Reinforcement Learning With Task Decomposition for Cooperative Multiagent Systems," in IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 5, pp. 2054-2065, May 2021, doi: 10.1109/TNNLS.2020.2996209.
• Z. Zhang, D. Wang and J. Gao, "Learning Automata-Based Multiagent Reinforcement Learning for Optimization of Cooperative Tasks," in IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 10, pp. 4639-4652, Oct. 2021, doi: 10.1109/TNNLS.2020.3025711.

Markov chain and Hidden Markov

• S. S. Hassan, S. Särkkä and Á. F. García-Fernández, "Temporal Parallelization of Inference in Hidden Markov Models," in IEEE Transactions on Signal Processing, vol. 69, pp. 4875-4887, 2021, doi: 10.1109/TSP.2021.3103338.
• A. M. Sainju, W. He and Z. Jiang, "A Hidden Markov Contour Tree Model for Spatial Structured Prediction," in IEEE Transactions on Knowledge and Data Engineering, vol. 34, no. 4, pp. 1530-1543, 1 April 2022, doi: 10.1109/TKDE.2020.3002887.
• H. Shi, et al.,"Semantics-Aware Hidden Markov Model for Human Mobility" in IEEE Transactions on Knowledge & Data Engineering, vol. 33, no. 03, pp. 1183-1194, 2021. doi: 10.1109/TKDE.2019.2937296

Clustering algorithm

• X. Jiang, S. Wei, T. Liu, R. Zhao, Y. Zhao and H. Huang, "Blind Image Clustering for Camera Source Identification via Row-Sparsity Optimization," in IEEE Transactions on Multimedia, vol. 23, pp. 2602-2613, 2021, doi: 10.1109/TMM.2020.3013449.
• W. Yang, X. Wang, J. Lu, W. Dou and S. Liu, "Interactive Steering of Hierarchical Clustering" in IEEE Transactions on Visualization & Computer Graphics, vol. 27, no. 10, pp. 3953-3967, 2021. doi: 10.1109/TVCG.2020.2995100
• Cai, Y., Zhang, Z., Cai, Z., Liu, X., Jiang, X., & Yan, Q. (2020). Graph convolutional subspace clustering: A robust subspace clustering framework for hyperspectral image. IEEE Transactions on Geoscience and Remote Sensing, 59(5), 4191-4202.

Bayesian learning

• S. Wang, J. Ren and R. Bai, "A Regularized Attribute Weighting Framework for Naive Bayes," in IEEE Access, vol. 8, pp. 225639-225649, 2020, doi: 10.1109/ACCESS.2020.3044946.
• Z. Zheng, X. Gao, X. Ma and G. Chen, "Predicting Hot Events in the Early Period through Bayesian Model for Social Networks," in IEEE Transactions on Knowledge and Data Engineering, vol. 34, no. 3, pp. 1390-1403, 1 March 2022, doi: 10.1109/TKDE.2020.2994946.