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Learning to Optimize: A Primer and A Benchmark

Mar 23, 2021
Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin

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Robust Reinforcement Learning for General Video Game Playing

Nov 11, 2020
Chengpeng Hu, Ziqi Wang, Tianye Shu, Yang Tao, Hao Tong, Julian Togelius, Xin Yao, Jialin Liu

* 10 pages, 4 figures.This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible 

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Deep Learning for Procedural Content Generation

Oct 09, 2020
Jialin Liu, Sam Snodgrass, Ahmed Khalifa, Sebastian Risi, Georgios N. Yannakakis, Julian Togelius

* Neural Computing and Applications 2020 (Early Access) 
* This is a pre-print of an article published in Neural Computing and Applications. The final authenticated version is available online at: 

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Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Jul 01, 2020
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, Arnold Overwijk

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A Hybrid Evolutionary Algorithm for Reliable Facility Location Problem

Jun 27, 2020
Han Zhang, Jialin Liu, Xin Yao

* Accepted at PPSN2020 

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Wavelet Scattering Networks for Atomistic Systems with Extrapolation of Material Properties

Jun 01, 2020
Paul Sinz, Michael W. Swift, Xavier Brumwell, Jialin Liu, Kwang Jin Kim, Yue Qi, Matthew Hirn

* 15 pages; 10 figures; 4 tables 

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Towards in-store multi-person tracking using head detection and track heatmaps

May 16, 2020
Aibek Musaev, Jiangping Wang, Liang Zhu, Cheng Li, Yi Chen, Jialin Liu, Wanqi Zhang, Juan Mei, De Wang

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A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros

May 14, 2020
Tianye Shu, Ziqi Wang, Jialin Liu, Xin Yao

* Accepted at IEEE CEC2020 

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Versatile Black-Box Optimization

Apr 29, 2020
Jialin Liu, Antoine Moreau, Mike Preuss, Baptiste Roziere, Jeremy Rapin, Fabien Teytaud, Olivier Teytaud

* Accepted at GECCO 2020 

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Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networks

Mar 31, 2020
Jacob Schrum, Jake Gutierrez, Vanessa Volz, Jialin Liu, Simon Lucas, Sebastian Risi

* GECCO 2020 

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Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration

Mar 06, 2020
Jian Kang, Danfeng Hong, Jialin Liu, Gerald Baier, Naoto Yokoya, Begüm Demir

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Task Augmentation by Rotating for Meta-Learning

Feb 08, 2020
Jialin Liu, Fei Chao, Chih-Min Lin

* 9 pages 

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Decoder Choice Network for Meta-Learning

Sep 25, 2019
Jialin Liu, Fei Chao, Longzhi Yang, Chih-Min Lin, Qiang Shen

* 13papers 

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Stock Prices Prediction using Deep Learning Models

Sep 25, 2019
Jialin Liu, Fei Chao, Yu-Chen Lin, Chih-Min Lin

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Gradient Boost with Convolution Neural Network for Stock Forecast

Sep 19, 2019
Jialin Liu, Chih-Min Lin, Fei Chao

* UKCL2019.11pages 

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Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale

Jul 08, 2019
Atılım Güneş Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip Torr, Victor Lee, Kyle Cranmer, Prabhat, Frank Wood

* 14 pages, 8 figures 

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Plug-and-Play Methods Provably Converge with Properly Trained Denoisers

May 14, 2019
Ernest K. Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin

* Published in the International Conference on Machine Learning, 2019 

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Algorithm Portfolio for Individual-based Surrogate-Assisted Evolutionary Algorithms

Apr 22, 2019
Hao Tong, Jialin Liu, Xin Yao

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Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor

Apr 03, 2019
Ivan Bravi, Simon Lucas, Diego Perez-Liebana, Jialin Liu

* Submitted to IEEE Conference on Games 2019 

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Voronoi-based Efficient Surrogate-assisted Evolutionary Algorithm for Very Expensive Problems

Jan 17, 2019
Hao Tong, Changwu Huang, Jialin Liu, Xin Yao

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Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best

Jan 03, 2019
Simon M. Lucas, Jialin Liu, Ivan Bravi, Raluca D. Gaina, John Woodward, Vanessa Volz, Diego Perez-Liebana

* 8 pages, to appear in 2019 AAAI workshop on Games and Simulations for Artificial Intelligence (

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Helix: Holistic Optimization for Accelerating Iterative Machine Learning

Dec 14, 2018
Doris Xin, Stephen Macke, Litian Ma, Jialin Liu, Shuchen Song, Aditya Parameswaran

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Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds

Nov 04, 2018
Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin

* 18 pages, 6 figures, 1 table. Accepted as spotlight oral in NIPS 2018 

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Helix: Accelerating Human-in-the-loop Machine Learning

Aug 03, 2018
Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya Parameswaran

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General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithms

Jul 27, 2018
Diego Perez-Liebana, Jialin Liu, Ahmed Khalifa, Raluca D. Gaina, Julian Togelius, Simon M. Lucas

* 20 pages, submitted to IEEE ToG 

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Deep Reinforcement Learning for General Video Game AI

Jun 06, 2018
Ruben Rodriguez Torrado, Philip Bontrager, Julian Togelius, Jialin Liu, Diego Perez-Liebana

* 8 pages, 4 figures, Accepted at the conference on Computational Intelligence and Games 2018 IEEE 

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Shallow decision-making analysis in General Video Game Playing

Jun 04, 2018
Ivan Bravi, Jialin Liu, Diego Perez-Liebana, Simon Lucas

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The N-Tuple Bandit Evolutionary Algorithm for Game Agent Optimisation

May 08, 2018
Simon M Lucas, Jialin Liu, Diego Perez-Liebana

* 9 pages, 3 figures, 3 table. This is the final version of the article accepted by WCCI2018 

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Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Network

May 02, 2018
Vanessa Volz, Jacob Schrum, Jialin Liu, Simon M. Lucas, Adam Smith, Sebastian Risi

* 8 pages, GECCO2018 

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