Learning to Multitask. CIKM (2017), Department of Computer Science and Engineering, Southern University of Science and Technology, Parameter Transfer Unit for Deep Neural Networks, Discriminative Distribution Alignment: A Unified Framework for Heterogeneous Domain Adaptation, Low-Resolution Image Categorization via Heterogeneous Domain Adaptation, A Component-based Diffusion Model with Structural Diversity for Social Networks, A Unified Framework for Epidemic Prediction based on Poisson Regression, Instance-Specific Canonical Correlation Analysis, A Regularization Approach to Learning Task Relationships in Multitask Learning, Transfer Metric Learning with Semi-Supervised Extension, Semisupervised Generalized Discriminant Analysis, Learning (from) Deep Hierarchical Structure among Features, Heterogeneous Domain Adaptation via Soft Transfer Network, Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification, Transfer Meets Hybrid: A Synthetic Approach for Cross-Domain Collaborative Filtering with Text, Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning, A Variational Autoencoder based Generative Model of Urban Human Mobility, Transfer Learning via Learning to Transfer, Personalizing a Dialogue System with Transfer Reinforcement Learning, Transferable Contextual Bandit for Cross-Domain Recommendation, Hierarchical Attention Transfer Network for Cross-domain Sentiment Classification, CoNet: Collaborative Cross Networks for Cross-Domain Recommendation, Multimodal Linear Discriminant Analysis via Structural Sparsity, End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification, Deep Neural Networks for High Dimension, Low Sample Size Data, Learning Sparse Task Relations in Multi-Task Learning, Fast Component Pursuit for Large-Scale Inverse Covariance Estimation, Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification in Flu Virus Data, Multi-Stage Multi-Task Learning with Reduced Rank, Reduction Techniques for Graph-based Convex Clustering, Learning Tree Structure in Multi-Task Learning, Differentially Private High-Dimensional Data Publishing via Sampling-Based Inference, Multi-Task Learning and Algorithmic Stability, Learning Multi-Level Task Groups in Multi-Task Learning, Encoding Tree Sparsity in Multi-Task Learning: A Probabilistic Framework, Heterogeneous-Neighborhood-based Multi-Task Local Learning Algorithms, Learning High-Order Task Relationships in Multi-Task Learning, Incorporating Structural Diversity of Neighbors in a Diffusion Model for Social Networks, Multi-Task Boosting by Exploiting Task Relationships, Overlapping Community Detection via Bounded Nonnegative Matrix Tri-Factorization, Supervised Probabilistic Robust Embedding with Sparse Noise, Multi-Task Learning in Heterogeneous Feature Spaces, Probabilistic Multi-Task Feature Selection, A Convex Formulation for Learning Task Relationships in Multi-Task Learning, Transfer Metric Learning by Learning Task Relationships, Multi-Task Warped Gaussian Process for Personalized Age Estimation, Heteroscedastic Probabilistic Linear Discriminant Analysis with Semi-Supervised Extension, Semi-Supervised Discriminant Analysis via CCCP, Semi-Supervised Discriminant Analysis using Robust Path-based Similarity, Learning from Facial Aging Patterns for Automatic Age Estimation, Distant Transfer Learning via Deep Random Walk, A Simple General Approach to Balance Task Difficulty in Multi-Task Learning, Deep Multi-Task Learning via Generalized Tensor Trace Norm, Deep Multi-Task Augmented Feature Learning via Hierarchical Graph Neural Network, Cross-domain Dialogue Policy Transfer via Simultaneous Speech-act and Slot Alignment, LCMR: Local and Centralized Memories for Collaborative Filtering with Unstructured Text, Fine Grained Knowledge Transfer for Personalized Task-Oriented Dialogue Systems, Integrating User and Agent Models: A Deep Task-Oriented Dialogue System, Transfer Learning, Multi-Task Learning and Cost-Sensitive Learning, Learning Inverse Dynamics by Gaussian Process Regression under the Multi-Task Learning Framework, A New Age Estimation Method based on Ensemble Learning.

45. (2014) Wang C*, Wei ZY*, Chen KY, Ye F, Yu C, Bennett V, Zhang MJ.

5, pp. Professor Zhang’s research interests include seismic wave forward modeling and inversion algorithm, strong ground motion, earth interior structure, and microseismic monitoring, etc. Prof. Xiaofei Chen, a renowned seismologist and an academician of Chinese Academy of Sciences (CAS), is appointed as an initiatory departmental head. 37.

Saeid Mofrad*, Ishtiaq Ahmed, Shiyong Lu, Ping Yang, Heming Cui, and Fengwei Zhang, "SecDATAVIEW: A Secure Big Data Workflow Management System for Heterogeneous Computing Environments", to appear in Proceedings of The 35th Annual Computer Security Applications Conference (ACSAC'19), San Juan, Puerto Rico, December, 2019. After receiving the project, he will sign a work agreement or labor contract with the Guangdong employer after exiting the station.

409-415, July 2017 5. 2009 Wei Zhang received the B.S.

Conejo, “On Resilience Analysis and Quantification for Wide-Area Control of Power Systems”, the 55th IEEE Conference on Decision and Control (CDC 2016), Las Vegas, NV, December 2016.

Sen Li*, Wei Zhang, Jianming Lian, and Karanjit Kalsi, “Market-based Coordination of Thermostatically Controlled Loads—Part I: A Mechanism Design Formulation”, IEEE Transactions on Power Systems, vol.

Department of Earth and Space Sciences.

.

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