b'Jialin Liu'

Learning to Optimize: A Primer and A Benchmark

Learning to optimize (L2O) is an emerging approach that leverages machin...
03/23/2021 ∙ by Tianlong Chen, et al. ∙ 61 ∙ share

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Robust Reinforcement Learning for General Video Game Playing

Reinforcement learning has successfully learned to play challenging boar...
11/11/2020 ∙ by Chengpeng Hu, et al. ∙ 39 ∙ share

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Deep Learning for Procedural Content Generation

Procedural content generation in video games has a long history. Existin...
10/09/2020 ∙ by Jialin Liu, et al. ∙ 28 ∙ share

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Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Conducting text retrieval in a dense learned representation space has ma...
07/01/2020 ∙ by Lee Xiong, et al. ∙ 0 ∙ share

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A Hybrid Evolutionary Algorithm for Reliable Facility Location Problem

The reliable facility location problem (RFLP) is an important research t...
06/27/2020 ∙ by Han Zhang, et al. ∙ 0 ∙ share

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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...
06/01/2020 ∙ by Paul Sinz, et al. ∙ 14 ∙ share

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

Computer vision algorithms are being implemented across a breadth of ind...
05/16/2020 ∙ by Aibek Musaev, et al. ∙ 8 ∙ share

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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 ...
05/13/2020 ∙ by Tianye Shu, et al. ∙ 2 ∙ share

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Versatile Black-Box Optimization

Choosing automatically the right algorithm using problem descriptors is ...
04/29/2020 ∙ by Jialin Liu, et al. ∙ 7 ∙ share

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

Generative Adversarial Networks (GANs) are an emerging form of indirect ...
03/31/2020 ∙ by Jacob Schrum, et al. ∙ 0 ∙ share

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Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration

Interferometric phase restoration has been investigated for decades and ...
03/06/2020 ∙ by Jian Kang, et al. ∙ 0 ∙ share

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Decoder Choice Network for Meta-Learning

Meta-learning has been widely used for implementing few-shot learning an...
09/25/2019 ∙ by Jialin Liu, et al. ∙ 16 ∙ share

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Stock Prices Prediction using Deep Learning Models

Financial markets have a vital role in the development of modern society...
09/25/2019 ∙ by Jialin Liu, et al. ∙ 0 ∙ share

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Gradient Boost with Convolution Neural Network for Stock Forecast

Market economy closely connects aspects to all walks of life. The stock ...
09/19/2019 ∙ by Jialin Liu, et al. ∙ 0 ∙ share

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Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale

Probabilistic programming languages (PPLs) are receiving widespread atte...
07/08/2019 ∙ by Atılım Güneş Baydin, et al. ∙ 2 ∙ share

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

Plug-and-play (PnP) is a non-convex framework that integrates modern den...
05/14/2019 ∙ by Ernest K. Ryu, et al. ∙ 9 ∙ share

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Algorithm Portfolio for Individual-based Surrogate-Assisted Evolutionary Algorithms

Surrogate-assisted evolutionary algorithms (SAEAs) are powerful optimisa...
04/22/2019 ∙ by Hao Tong, et al. ∙ 8 ∙ share

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Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor

Game-based benchmarks have been playing an essential role in the develop...
04/03/2019 ∙ by Ivan Bravi, et al. ∙ 10 ∙ share

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

Very expensive problems are very common in practical system that one fit...
01/17/2019 ∙ by Hao Tong, et al. ∙ 0 ∙ share

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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...
01/03/2019 ∙ by Simon M. Lucas, et al. ∙ 20 ∙ share

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Helix: Holistic Optimization for Accelerating Iterative Machine Learning

Machine learning workflow development is a process of trial-and-error: d...
12/14/2018 ∙ by Doris Xin, et al. ∙ 0 ∙ share

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

We propose a fast algorithm for the calculation of the Wasserstein-1 dis...
09/29/2018 ∙ by Jialin Liu, et al. ∙ 1 ∙ share

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

In recent years, unfolding iterative algorithms as neural networks has b...
08/29/2018 ∙ by Xiaohan Chen, et al. ∙ 5 ∙ share

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

Data application developers and data scientists spend an inordinate amou...
08/03/2018 ∙ by Doris Xin, et al. ∙ 0 ∙ share

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Deep Reinforcement Learning for General Video Game AI

The General Video Game AI (GVGAI) competition and its associated softwar...
06/06/2018 ∙ by Ruben Rodriguez Torrado, et al. ∙ 12 ∙ share

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Shallow decision-making analysis in General Video Game Playing

The General Video Game AI competitions have been the testing ground for ...
06/04/2018 ∙ by Ivan Bravi, et al. ∙ 0 ∙ share

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

Generative Adversarial Networks (GANs) are a machine learning approach c...
05/02/2018 ∙ by Vanessa Volz, et al. ∙ 0 ∙ share

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

Development of machine learning (ML) workflows is a tedious process of i...
04/16/2018 ∙ by Doris Xin, et al. ∙ 0 ∙ share

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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...
02/28/2018 ∙ by Diego Pérez-Liébana, et al. ∙ 0 ∙ share

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

This paper proposes an agent with particle swarm optimization (PSO) base...
02/24/2018 ∙ by Chang-Shing Lee, et al. ∙ 0 ∙ share

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The N-Tuple Bandit Evolutionary Algorithm for Game Agent Optimisation

This paper describes the N-Tuple Bandit Evolutionary Algorithm (NTBEA), ...
02/16/2018 ∙ by Simon M. Lucas, et al. ∙ 0 ∙ share

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Online Convolutional Dictionary Learning

Convolutional sparse representations are a form of sparse representation...
08/31/2017 ∙ by Jialin Liu, et al. ∙ 0 ∙ share

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Efficient Noisy Optimisation with the Sliding Window Compact Genetic Algorithm

The compact genetic algorithm is an Estimation of Distribution Algorithm...
08/07/2017 ∙ by Simon M. Lucas, et al. ∙ 0 ∙ share

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Evaluating Noisy Optimisation Algorithms: First Hitting Time is Problematic

A key part of any evolutionary algorithm is fitness evaluation. When fit...
06/13/2017 ∙ by Simon M. Lucas, et al. ∙ 0 ∙ share

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

HPC applications pose high demands on I/O performance and storage capabi...
05/10/2017 ∙ by Wei Liu, et al. ∙ 0 ∙ share

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

Monte Carlo Tree Search techniques have generally dominated General Vide...
04/24/2017 ∙ by Raluca D. Gaina, et al. ∙ 0 ∙ share

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Automatically Reinforcing a Game AI

A recent research trend in Artificial Intelligence (AI) is the combinati...
07/27/2016 ∙ by David L. St-Pierre, et al. ∙ 1 ∙ share

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Optimal resampling for the noisy OneMax problem

The OneMax problem is a standard benchmark optimisation problem for a bi...
07/22/2016 ∙ by Jialin Liu, et al. ∙ 0 ∙ share

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

Many artificial intelligences (AIs) are randomized. One can be lucky or ...
07/08/2016 ∙ by Tristan Cazenave, et al. ∙ 0 ∙ share

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Rolling Horizon Coevolutionary Planning for Two-Player Video Games

This paper describes a new algorithm for decision making in two-player r...
07/06/2016 ∙ by Jialin Liu, et al. ∙ 0 ∙ share

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Bandit-Based Random Mutation Hill-Climbing

The Random Mutation Hill-Climbing algorithm is a direct search technique...
06/20/2016 ∙ by Jialin Liu, et al. ∙ 0 ∙ share

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

Consider convex optimization problems subject to a large number of const...
11/12/2015 ∙ by Mengdi Wang, et al. ∙ 0 ∙ share

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Jialin Liu

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