b'Jialin Liu'

research

∙ 07/05/2022

Generating Game Levels of Diverse Behaviour Engagement

Recent years, there has been growing interests in experience-driven proc...

Keyuan Zhang, et al. ∙

research

∙ 10/29/2021

Hyperparameter Tuning is All You Need for LISTA

Learned Iterative Shrinkage-Thresholding Algorithm (LISTA) introduces th...

Xiaohan Chen, et al. ∙

research

∙ 10/11/2021

Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection

Robust principal component analysis (RPCA) is a critical tool in modern ...

HanQin Cai, et al. ∙

research

∙ 07/07/2021

Keiki: Towards Realistic Danmaku Generation via Sequential GANs

Search-based procedural content generation methods have recently been in...

Ziqi Wang, et al. ∙

research

∙ 06/30/2021

Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study

We introduce a procedural content generation (PCG) framework at the inte...

Tianye Shu, et al. ∙

research

∙ 03/23/2021

Learning to Optimize: A Primer and A Benchmark

Learning to optimize (L2O) is an emerging approach that leverages machin...

Tianlong Chen, et al. ∙

research

∙ 11/11/2020

Robust Reinforcement Learning for General Video Game Playing

Reinforcement learning has successfully learned to play challenging boar...

Chengpeng Hu, et al. ∙

research

∙ 10/09/2020

Deep Learning for Procedural Content Generation

Procedural content generation in video games has a long history. Existin...

Jialin Liu, et al. ∙

research

∙ 07/01/2020

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Conducting text retrieval in a dense learned representation space has ma...

Lee Xiong, et al. ∙

research

∙ 06/27/2020

A Hybrid Evolutionary Algorithm for Reliable Facility Location Problem

The reliable facility location problem (RFLP) is an important research t...

Han Zhang, et al. ∙

research

∙ 06/01/2020

Wavelet Scattering Networks for Atomistic Systems with Extrapolation of Material Properties

The dream of machine learning in materials science is for a model to lea...

Paul Sinz, et al. ∙

research

∙ 05/16/2020

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

Computer vision algorithms are being implemented across a breadth of ind...

Aibek Musaev, et al. ∙

research

∙ 05/13/2020

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

Applying latent variable evolution to game level design has become more ...

Tianye Shu, et al. ∙

research

∙ 04/29/2020

Versatile Black-Box Optimization

Choosing automatically the right algorithm using problem descriptors is ...

Jialin Liu, et al. ∙

research

∙ 03/31/2020

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

Generative Adversarial Networks (GANs) are an emerging form of indirect ...

Jacob Schrum, et al. ∙

research

∙ 03/06/2020

Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration

Interferometric phase restoration has been investigated for decades and ...

Jian Kang, et al. ∙

research

∙ 09/25/2019

Decoder Choice Network for Meta-Learning

Meta-learning has been widely used for implementing few-shot learning an...

Jialin Liu, et al. ∙

research

∙ 09/25/2019

Stock Prices Prediction using Deep Learning Models

Financial markets have a vital role in the development of modern society...

Jialin Liu, et al. ∙

research

∙ 09/19/2019

Gradient Boost with Convolution Neural Network for Stock Forecast

Market economy closely connects aspects to all walks of life. The stock ...

Jialin Liu, et al. ∙

research

∙ 07/08/2019

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale

Probabilistic programming languages (PPLs) are receiving widespread atte...

Atılım Güneş Baydin, et al. ∙

research

∙ 05/14/2019

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

Plug-and-play (PnP) is a non-convex framework that integrates modern den...

Ernest K. Ryu, et al. ∙

research

∙ 04/22/2019

Algorithm Portfolio for Individual-based Surrogate-Assisted Evolutionary Algorithms

Surrogate-assisted evolutionary algorithms (SAEAs) are powerful optimisa...

Hao Tong, et al. ∙

research

∙ 04/03/2019

Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor

Game-based benchmarks have been playing an essential role in the develop...

Ivan Bravi, et al. ∙

research

∙ 01/17/2019

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

Very expensive problems are very common in practical system that one fit...

Hao Tong, et al. ∙

research

∙ 01/03/2019

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

This paper introduces a simple and fast variant of Planet Wars as a test...

Simon M. Lucas, et al. ∙

research

∙ 12/14/2018

Helix: Holistic Optimization for Accelerating Iterative Machine Learning

Machine learning workflow development is a process of trial-and-error: d...

Doris Xin, et al. ∙

research

∙ 09/29/2018

Multilevel Optimal Transport: a Fast Approximation of Wasserstein-1 distances

We propose a fast algorithm for the calculation of the Wasserstein-1 dis...

Jialin Liu, et al. ∙

research

∙ 08/29/2018

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

In recent years, unfolding iterative algorithms as neural networks has b...

Xiaohan Chen, et al. ∙

research

∙ 08/03/2018

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

Data application developers and data scientists spend an inordinate amou...

Doris Xin, et al. ∙

research

∙ 06/06/2018

Deep Reinforcement Learning for General Video Game AI

The General Video Game AI (GVGAI) competition and its associated softwar...

Ruben Rodriguez Torrado, et al. ∙

research

∙ 06/04/2018

Shallow decision-making analysis in General Video Game Playing

The General Video Game AI competitions have been the testing ground for ...

Ivan Bravi, et al. ∙

research

∙ 05/02/2018

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

Generative Adversarial Networks (GANs) are a machine learning approach c...

Vanessa Volz, et al. ∙

research

∙ 04/16/2018

Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities

Development of machine learning (ML) workflows is a tedious process of i...

Doris Xin, et al. ∙

research

∙ 02/28/2018

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

General Video Game Playing (GVGP) aims at designing an agent that is cap...

Diego Pérez-Liébana, et al. ∙

research

∙ 02/24/2018

PSO-based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application

This paper proposes an agent with particle swarm optimization (PSO) base...

Chang-Shing Lee, et al. ∙

research

∙ 02/16/2018

The N-Tuple Bandit Evolutionary Algorithm for Game Agent Optimisation

This paper describes the N-Tuple Bandit Evolutionary Algorithm (NTBEA), ...

Simon M. Lucas, et al. ∙

research

∙ 08/31/2017

Online Convolutional Dictionary Learning

Convolutional sparse representations are a form of sparse representation...

Jialin Liu, et al. ∙

research

∙ 08/07/2017

Efficient Noisy Optimisation with the Sliding Window Compact Genetic Algorithm

The compact genetic algorithm is an Estimation of Distribution Algorithm...

Simon M. Lucas, et al. ∙

research

∙ 06/13/2017

Evaluating Noisy Optimisation Algorithms: First Hitting Time is Problematic

A key part of any evolutionary algorithm is fitness evaluation. When fit...

Simon M. Lucas, et al. ∙

research

∙ 05/10/2017

Performance Evaluation and Modeling of HPC I/O on Non-Volatile Memory

HPC applications pose high demands on I/O performance and storage capabi...

Wei Liu, et al. ∙

research

∙ 04/24/2017

Analysis of Vanilla Rolling Horizon Evolution Parameters in General Video Game Playing

Monte Carlo Tree Search techniques have generally dominated General Vide...

Raluca D. Gaina, et al. ∙

research

∙ 07/27/2016

Automatically Reinforcing a Game AI

A recent research trend in Artificial Intelligence (AI) is the combinati...

David L. St-Pierre, et al. ∙

research

∙ 07/22/2016

Optimal resampling for the noisy OneMax problem

The OneMax problem is a standard benchmark optimisation problem for a bi...

Jialin Liu, et al. ∙

research

∙ 07/08/2016

Learning opening books in partially observable games: using random seeds in Phantom Go

Many artificial intelligences (AIs) are randomized. One can be lucky or ...

Tristan Cazenave, et al. ∙

research

∙ 07/06/2016

Rolling Horizon Coevolutionary Planning for Two-Player Video Games

This paper describes a new algorithm for decision making in two-player r...

Jialin Liu, et al. ∙

research

∙ 06/20/2016

Bandit-Based Random Mutation Hill-Climbing

The Random Mutation Hill-Climbing algorithm is a direct search technique...

Jialin Liu, et al. ∙

research

∙ 11/12/2015

Random Multi-Constraint Projection: Stochastic Gradient Methods for Convex Optimization with Many Constraints

Consider convex optimization problems subject to a large number of const...

Mengdi Wang, et al. ∙

Jialin Liu

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