Lu Bai

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Beihang University

Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks

Joint-event-extraction, which extracts structural information (i.e., ent...
10/13/2020 ∙ by Yue Wang, et al. ∙ 0 ∙ share

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A Big Data Enabled Channel Model for 5G Wireless Communication Systems

The standardization process of the fifth generation (5G) wireless commun...
02/28/2020 ∙ by Jie Huang, et al. ∙ 0 ∙ share

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A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs

In this paper, we develop a new graph kernel, namely the Hierarchical Tr...
02/08/2020 ∙ by Lu Bai, et al. ∙ 0 ∙ share

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Generative Temporal Link Prediction via Self-tokenized Sequence Modeling

We formalize networks with evolving structures as temporal networks and ...
11/26/2019 ∙ by Yue Wang, et al. ∙ 11 ∙ share

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A Multi-Task Gradient Descent Method for Multi-Label Learning

Multi-label learning studies the problem where an instance is associated...
11/18/2019 ∙ by Lu Bai, et al. ∙ 0 ∙ share

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Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis

In this work, we develop a novel framework to measure the similarity bet...
10/21/2019 ∙ by Lu Bai, et al. ∙ 0 ∙ share

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Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking

Counterfactual thinking describes a psychological phenomenon that people...
08/13/2019 ∙ by Yue Wang, et al. ∙ 7 ∙ share

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A Quantum-inspired Similarity Measure for the Analysis of Complete Weighted Graphs

We develop a novel method for measuring the similarity between complete ...
04/28/2019 ∙ by Lu Bai, et al. ∙ 0 ∙ share

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Fused Lasso for Feature Selection using Structural Information

Feature selection has been proven a powerful preprocessing step for high...
02/26/2019 ∙ by Lixin Cui, et al. ∙ 0 ∙ share

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Learning Vertex Convolutional Networks for Graph Classification

In this paper, we develop a new aligned vertex convolutional network mod...
02/26/2019 ∙ by Lu Bai, et al. ∙ 0 ∙ share

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Deep Co-investment Network Learning for Financial Assets

Most recent works model the market structure of the stock market as a co...
09/12/2018 ∙ by Yue Wang, et al. ∙ 0 ∙ share

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Identifying The Most Informative Features Using A Structurally Interacting Elastic Net

Feature selection can efficiently identify the most informative features...
09/08/2018 ∙ by Lixin Cui, et al. ∙ 0 ∙ share

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A Quantum Spatial Graph Convolutional Neural Network using Quantum Passing Information

In this paper, we develop a new Quantum Spatial Graph Convolutional Neur...
09/04/2018 ∙ by Lu Bai, et al. ∙ 0 ∙ share

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Lu Bai

Featured Co-authors

Philip S. Yu

Yang Yang

Yue Wang

Jian Sun

Jie Li

Abhishek Gupta

Jian Cheng

Yew Soon Ong

Qian Zhao

Shu Wu

Chenwei Zhang

Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks

A Big Data Enabled Channel Model for 5G Wireless Communication Systems

A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs

Generative Temporal Link Prediction via Self-tokenized Sequence Modeling

A Multi-Task Gradient Descent Method for Multi-Label Learning

Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking

A Quantum-inspired Similarity Measure for the Analysis of Complete Weighted Graphs

Fused Lasso for Feature Selection using Structural Information

Learning Vertex Convolutional Networks for Graph Classification

Deep Co-investment Network Learning for Financial Assets

Identifying The Most Informative Features Using A Structurally Interacting Elastic Net

A Quantum Spatial Graph Convolutional Neural Network using Quantum Passing Information