Check Google Scholar for a compact list. * denotes equal contribution
Papers
REVISITING HETEROPHILY FOR GRAPH NEURAL NETWORKS
Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup @ Conference on Neural Information Processing Systems (NeurIPS), 2022
TEMPORAL ABSTRACTIONS-AUGMENTED TEMPORALLY CONTRASTIVE LEARNING: AN ALTERNATIVE TO THE LAPLACIAN IN RL
Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio @ Conference on Uncertainty in Artificial Intelligence (UAI), 2022
A CONSCIOUSNESS-INSPIRED PLANNING AGENT FOR MODEL-BASED REINFORCEMENT LEARNING
Mingde Zhao*, Zhen Liu*, Sitao Luan*, Shuyuan Zhang*, Doina Precup, Yoshua Bengio @ Conference on Neural Information Processing Systems (NeurIPS), 2021.
BI-SPACE INTERACTIVE COOPERATIVE COEVOLUTIONARY ALGORITHM FOR LARGE SCALE BLACKBOX OPTIMIZATION
Hongwei Ge, Mingde Zhao, Yaqing Hou, Kai Zhang, Liang Sun, Guozhen Tan, Qiang Zhang, Philip Chen @ Applied Soft Computing, 2020
TRAINING MATTERS: UNLOCKING POTENTIALS OF DEEPER GRAPH CONVOLUTIONAL NEURAL NETWORKS
Sitao Luan*, Mingde Zhao*, Xiao-Wen Chang, Doina Precup @ ArXiv, 2020.
COMPLETE THE MISSING HALF: AUGMENTING AGGREGATION FILTERING WITH DIVERSIFICATION FOR GRAPH CONVOLUTIONAL NETWORKS
Sitao Luan*, Mingde Zhao*, Chenqing Hua*, Xiao-Wen Chang, Doina Precup @ ArXiv, 2020.
TWO-STAGE AUTOMATIC IMAGE ANNOTATION BASED ON LATENT SEMANTIC SCENE CLASSIFICATION
Hongwei Ge, Kai Zhang, Yaqing Hou, Chao Yu, Mingde Zhao, Zhen Wang, Liang Sun @ International Joint Conference on Neural Networks (IJCNN), 2020.
META-LEARNING STATE-BASED ELIGIBILITY TRACES FOR MORE SAMPLE-EFFICIENT POLICY EVALUATION
Mingde Zhao*, Sitao Luan*, Ian Porada*, Xiao-Wen Chang, Doina Precup @ International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020.
BREAK THE CEILING: STRONGER MULTI-SCALE DEEP GRAPH CONVOLUTIONAL NETWORKS
Sitao Luan*, Mingde Zhao*, Xiao-Wen Chang, Doina Precup @ Conference on Neural Information Processing Systems (NeurIPS), 2019.
EXPLORING OVERALL CONTEXTUAL INFORMATION FOR IMAGE CAPTIONING IN HUMAN-LIKE COGNITIVE STYLE
Hongwei Ge, Zehang Yan, Kai Zhang, Mingde Zhao, Liang Sun @ International Conference on Computer Vision (ICCV), 2019.
A TWO-ENGINE INTERACTION DRIVEN MANY-OBJECTIVE EVOLUTIONARY ALGORITHM WITH FEASIBILITY-AWARE ADAPTATION
Hongwei Ge*, Mingde Zhao*, Kai Zhang, Yaqing Hou @ Applied Soft Computing, 2019.
STACKED DENOISING EXTREME LEARNING MACHINE AUTOENCODER BASED ON GRAPH EMBEDDING FOR FEATURE REPRESENTATION
Hongwei Ge, Weiting Sun, Mingde Zhao, Yao Yao @ IEEE Access, 2019.
GENERALIZABLE META-HEURISTIC BASED ON TEMPORAL ESTIMATION OF REWARDS FOR LARGE SCALE BLACKBOX OPTIMIZATION
Mingde Zhao, Hongwei Ge, Yi Lian, Kai Zhang @ ArXiv, 2019.
STRATEGY SELECTION IN COMPLEX GAME ENVIRONMENTS BASED ON TRANSFER RL
Hongwei Ge*, Mingde Zhao*, Kai Zhang, Liang Sun @ International Joint Conference on Neural Networks (IJCNN), 2019.
MULTI-GRAINED CASCADE ADABOOST EXTREME LEARNING MACHINE FOR FEATURE REPRESENTATION
Hongwei Ge, Weiting Sun, Mingde Zhao, Kai Zhang, Liang Sun, Chao Yu @ International Joint Conference on Neural Networks (IJCNN), 2019.
A SELECTIVE ENSEMBLE LEARNING FRAMEWORK FOR ECG-BASED HEARTBEAT CLASSIFICATION WITH IMBALANCED DATA
Hongwei Ge, Keyi Sun, Liang Sun, Mingde Zhao, Chunguo Wu @ International Conference on Bioinformatics and Biomedicine (BIBM), 2018.
A MANY-OBJECTIVE EVOLUTIONARY ALGORITHM WITH TWO INTERACTING PROCESSES: CASCADE CLUSTERING AND REFERENCE POINT INCREMENTAL LEARNING
Hongwei Ge*, Mingde Zhao*, Liang Sun, Zhen Wang, Guozhen Tan, Qiang Zhang, C. L. Philip Chen @ IEEE Transactions on Evolutionary Computation (TEVC), 2019.
A MANY-OBJECTIVE EVOLUTIONARY ALGORITHM WITH FAST CLUSTERING AND REFERENCE POINT REDISTRIBUTION
Mingde Zhao, Hongwei Ge, Hongyan Han, Liang Sun @ IEEE Congress on Evolutionary Computation (CEC), 2018.
Software and Patents
FAST DICHOTOMIC CNN FOR HIERARCHICAL TRAFFIC SIGN IDENTIFICATION
Hongwei Ge, Mingde Zhao @ National Intellectual Property Administration of China, 2017.
PEACH FLESH SEGMENTATION USING DRL
Hongwei Ge, Mingde Zhao @ National Intellectual Property Administration of China, 2017.
Theses
META-LEARNING ELIGIBILITY TRACES FOR MORE SAMPLE EFFICIENT TEMPORAL DIFFERENCE LEARNING
Mingde Zhao @ McGill University, Master Thesis, 2020.
A TRANSFER RL MODEL BASED ON KNOWLEDGE INHERITANCE AND DECISION-MAKING ASSISTANCE
Mingde Zhao @ Dalian University of Technology, Undergraduate Thesis, 2018.