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Efficient Combinatorial Optimization for Word-level Adversarial Textual Attack


Sep 06, 2021
Shengcai Liu, Ning Lu, Cheng Chen, Ke Tang


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Deep Sequence Modeling: Development and Applications in Asset Pricing


Aug 20, 2021
Lin William Cong, Ke Tang, Jingyuan Wang, Yang Zhang


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Active Reinforcement Learning over MDPs


Aug 17, 2021
Qi Yang, Peng Yang, Ke Tang

* In this version, we ignored a prior related work as our baseline, and need to update corresponding reviews and experiments in next version 

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Multi-Domain Active Learning: A Comparative Study


Jun 25, 2021
Rui He, Shan He, Ke Tang


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Robust Dynamic Network Embedding via Ensembles


May 30, 2021
Chengbin Hou, Guoji Fu, Peng Yang, Shan He, Ke Tang


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Multi-objective Evolutionary Algorithms are Generally Good: Maximizing Monotone Submodular Functions over Sequences


Apr 20, 2021
Chao Qian, Dan-Xuan Liu, Chao Feng, Ke Tang


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A New Knowledge Gradient-based Method for Constrained Bayesian Optimization


Jan 20, 2021
Wenjie Chen, Shengcai Liu, Ke Tang

* 14 pages, 0 figures 

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A Survey on Neural Network Interpretability


Dec 28, 2020
Yu Zhang, Peter Tiňo, Aleš Leonardis, Ke Tang


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Memetic Search for Vehicle Routing with Simultaneous Pickup-Delivery and Time Windows


Nov 19, 2020
Shengcai Liu, Ke Tang, Xin Yao


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Interpreting Deep Learning Model Using Rule-based Method


Oct 15, 2020
Xiaojian Wang, Jingyuan Wang, Ke Tang


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Evolutionary Reinforcement Learning via Cooperative Coevolutionary Negatively Correlated Search


Sep 08, 2020
Hu Zhang, Peng Yang, Yanglong Yu, Mingjia Li, Ke Tang


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GloDyNE: Global Topology Preserving Dynamic Network Embedding


Aug 05, 2020
Chengbin Hou, Han Zhang, Shan He, Ke Tang

* Major revision, TKDE 

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Few-shots Parameter Tuning via Co-evolution


Jul 01, 2020
Ke Tang, Shengcai Liu, Peng Yang, Xin Yao


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On Performance Estimation in Automatic Algorithm Configuration


Nov 19, 2019
Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao

* accepted by AAAI 2020 

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Negatively Correlated Search as a Parallel Exploration Search Strategy


Oct 16, 2019
Peng Yang, Ke Tang, Xin Yao


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Competitive Co-evolution for Dynamic Constrained Optimisation


Jul 31, 2019
Xiaofen Lu, Ke Tang, Stefan Menzel, Xin Yao


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DynWalks: Global Topology and Recent Changes Awareness Dynamic Network Embedding


Jul 27, 2019
Chengbin Hou, Han Zhang, Ke Tang, Shan He

* 14 pages, 7 figures, 5 tables 

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AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks


Jul 24, 2019
Jingyuan Wang, Yang Zhang, Ke Tang, Junjie Wu, Zhang Xiong

* Accepted for POSTER presentation at KDD2019 Applied Data Science Track 

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Running Time Analysis of the (1+1)-EA for Robust Linear Optimization


Jun 17, 2019
Chao Bian, Chao Qian, Ke Tang

* 17 pages, 1 table 

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Decision Making with Machine Learning and ROC Curves


May 05, 2019
Kai Feng, Han Hong, Ke Tang, Jingyuan Wang


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Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions


Mar 10, 2019
Yunwen Lei, Ting Hu, Guiying Li, Ke Tang


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A Parallel Divide-and-Conquer based Evolutionary Algorithm for Large-scale Optimization


Dec 06, 2018
Peng Yang, Ke Tang, Xin Yao

* 12 pages, 0 figures 

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Attributed Network Embedding for Incomplete Structure Information


Nov 28, 2018
Chengbin Hou, Shan He, Ke Tang

* 8 pages, 5 figures 

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Maximizing Monotone DR-submodular Continuous Functions by Derivative-free Optimization


Oct 16, 2018
Yibo Zhang, Chao Qian, Ke Tang


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Analysis of Noisy Evolutionary Optimization When Sampling Fails


Oct 11, 2018
Chao Qian, Chao Bian, Yang Yu, Ke Tang, Xin Yao


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Automatic Construction of Parallel Portfolios via Explicit Instance Grouping


Apr 17, 2018
Shengcai Liu, Ke Tang, Xin Yao


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