no code implementations • 30 May 2023 • Chaozhong Xue, Yongqi Dong, Jiaqi Liu, Yijun Liao, Lingbo Li
To tackle the emerging challenges, this study designs a reverse logistics system architecture with three modules, i. e., medical waste classification & monitoring module, temporary storage & disposal site (disposal site for short) selection module, as well as route optimization module.
no code implementations • 9 Feb 2023 • Chaozhong Xue, Yongqi Dong, Jiaqi Liu, Yijun Liao, Lingbo Li
To tackle the challenges, this study proposes a reverse logistics system architecture with three modules, i. e., medical waste classification & monitoring module, temporary storage & disposal site (disposal site for short) selection module, as well as route optimization module.
no code implementations • 20 Dec 2022 • Lingbo Li, Leslie Kanthan, Michail Basios, Fan Wu, Manal Adham, Vitali Avagyan, Alexis Butler, Paul Brookes, Rafail Giavrimis, Buhong Liu, Chrystalla Pavlou, Matthew Truscott, Vardan Voskanyan
Additionally, a key feature of evoML is that it embeds code and model optimisation into the model development process, and includes multi-objective optimisation capabilities.
no code implementations • 1 Aug 2022 • Lingbo Li, Tianle Li, Xinyi He, Mengyu Zhou, Shi Han, Dongmei Zhang
ASTA framework extracts data features by designing signatures based on expert knowledge, and enables data referencing at field- (chart) or cell-level (conditional formatting) with pre-trained models.
no code implementations • 16 Sep 2020 • Fan Fang, Carmine Ventre, Lingbo Li, Leslie Kanthan, Fan Wu, Michail Basios
Feature importance aims at measuring how crucial each input feature is for model prediction.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+3
no code implementations • 10 Sep 2020 • Yuxi Huan, Fan Wu, Michail Basios, Leslie Kanthan, Lingbo Li, Baowen Xu
In this paper, we introduce an intelligent evolutionary optimisation algorithm which applies machine learning technique to the traditional evolutionary algorithm to accelerate the overall optimisation process of tuning machine learning models in classification problems.
no code implementations • 25 Mar 2020 • Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, Lingbo Li, David Martinez-Regoband, Fan Wu
This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e. g., cryptocurrency trading systems, bubble and extreme conditions, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).
no code implementations • 9 Feb 2020 • Fan Fang, Waichung Chung, Carmine Ventre, Michail Basios, Leslie Kanthan, Lingbo Li, Fan Wu
The cryptocurrency market is amongst the fastest-growing of all the financial markets in the world.