activity
20162020
most citedStock Prices Prediction using Deep Learning Models

18 citations · 51 across the 9 of their papers we have counts for

collaborators

16 papers

cs.CV20201 cited

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

Aibek Musaev, Jiangping Wang, Liang Zhu +6

Computer vision algorithms are being implemented across a breadth of industries to enable technological innovations. In this paper, we study the problem of computer vision based cu…

cs.LG201918 cited

Stock Prices Prediction using Deep Learning Models

Jialin Liu, Fei Chao, Yu-Chen Lin +1

Financial markets have a vital role in the development of modern society. They allow the deployment of economic resources. Changes in stock prices reflect changes in the market. In…

cs.LG2019

Gradient Boost with Convolution Neural Network for Stock Forecast

Jialin Liu, Chih-Min Lin, Fei Chao

Market economy closely connects aspects to all walks of life. The stock forecast is one of task among studies on the market economy. However, information on markets economy contain…

cs.LG2019

Decoder Choice Network for Meta-Learning

Jialin Liu, Fei Chao, Longzhi Yang +2

Meta-learning has been widely used for implementing few-shot learning and fast model adaptation. One kind of meta-learning methods attempt to learn how to control the gradient desc…

cs.AI20194 cited

Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor

Ivan Bravi, Simon Lucas, Diego Perez-Liebana +1

Game-based benchmarks have been playing an essential role in the development of Artificial Intelligence (AI) techniques. Providing diverse challenges is crucial to push research to…

cs.AI201917 cited

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

Simon M. Lucas, Jialin Liu, Ivan Bravi +4

This paper introduces a simple and fast variant of Planet Wars as a test-bed for statistical planning based Game AI agents, and for noisy hyper-parameter optimisation. Planet Wars…