|
|
|
|
|
Parisa Mahya and Johannes Fürnkranz
Recently, some effort went into explaining intransparent and black-box models, such as deep neural networks or random forests. So-called model-agnostic methods typically approximate the prediction of the intransparent black-box model with an interpretabl...
ver más
|
|
|
|
|
|
|
|
|
|
|
Gulsum Alicioglu and Bo Sun
Deep learning (DL) models have achieved state-of-the-art performance in many domains. The interpretation of their working mechanisms and decision-making process is essential because of their complex structure and black-box nature, especially for sensitiv...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhengyang Fan, Wanru Li, Kathryn Blackmond Laskey and Kuo-Chu Chang
Phishing attacks represent a significant and growing threat in the digital world, affecting individuals and organizations globally. Understanding the various factors that influence susceptibility to phishing is essential for developing more effective str...
ver más
|
|
|
|
|
|
|
|
|
|
|
Manuel Zamudio López, Hamidreza Zareipour and Mike Quashie
This research proposes an investigative experiment employing binary classification for short-term electricity price spike forecasting. Numerical definitions for price spikes are derived from economic and statistical thresholds. The predictive task employ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chenbo Fu, Xingyu Pan, Xuejiao Liang, Shanqing Yu, Xiaoke Xu and Yong Min
In recent years, fake news detection and its characteristics have attracted a number of researchers. However, most detection algorithms are driven by data rather than theories, which causes the existing approaches to only perform well on specific dataset...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kun Kang, Qishen Chen, Kun Wang, Yanfei Zhang, Dehui Zhang, Guodong Zheng, Jiayun Xing, Tao Long, Xin Ren, Chenghong Shang and Bojing Cui
In the context of globalization in the mining industry, assessing the production feasibility of mining projects by smart technology is crucial for the improvement of mining development efficiency. However, evaluating the feasibility of such projects face...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sangwan Lee, Jicheol Yang, Kuk Cho and Dooyong Cho
This study explored how transportation accessibility and traffic volumes for automobiles, buses, and trucks are related. This study employed machine learning techniques, specifically the extreme gradient boosting decision tree model (XGB) and Shapley Val...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yiji Ma, Yuzhe Zhao, Jiahao Yu, Jingmiao Zhou and Haibo Kuang
Shipping companies and maritime organizations want to improve the energy efficiency of ships and reduce fuel costs through optimization measures; however, the accurate fuel consumption prediction of fuel consumption is a prerequisite for conducting optim...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mohit Kumar, Bernhard A. Moser, Lukas Fischer and Bernhard Freudenthaler
In order to develop machine learning and deep learning models that take into account the guidelines and principles of trustworthy AI, a novel information theoretic approach is introduced in this article. A unified approach to privacy-preserving interpret...
ver más
|
|
|
|
|
|
|
|
|
|
|
Catur Supriyanto, Abu Salam, Junta Zeniarja and Adi Wijaya
This research paper presents a deep-learning approach to early detection of skin cancer using image augmentation techniques. We introduce a two-stage image augmentation process utilizing geometric augmentation and a generative adversarial network (GAN) t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rohan Kumar Yadav and Dragos Constantin Nicolae
Explainability is one of the key factors in Natural Language Processing (NLP) specially for legal documents, medical diagnosis, and clinical text. Attention mechanism has been a popular choice for such explainability recently by estimating the relative i...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shuangzhong Wang and Ying Zhang
The federated learning network requires all the connection weights to be shared among the server and clients during training which increases the risk of data leakage. Meanwhile, the traditional federated learning method has a poor diagnostic effect for n...
ver más
|
|
|
|
|
|
|
|
|
|
|
Cheng Zhang, Xiong Zou and Chuan Lin
In order to prevent safety risks, control marine accidents and improve the overall safety of marine navigation, this study established a marine accident prediction model. The influences of management characteristics, environmental characteristics, person...
ver más
|
|
|
|
|
|
|
|
|
|
|
Roberto Vega, Leonardo Flores and Russell Greiner
Accurate forecasts of the number of newly infected people during an epidemic are critical for making effective timely decisions. This paper addresses this challenge using the SIMLR model, which incorporates machine learning (ML) into the epidemiological ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiamu Li, Ji Zhang, Mohamed Jaward Bah, Jian Wang, Youwen Zhu, Gaoming Yang, Lingling Li and Kexin Zhang
When dealing with high-dimensional data, such as in biometric, e-commerce, or industrial applications, it is extremely hard to capture the abnormalities in full space due to the curse of dimensionality. Furthermore, it is becoming increasingly complicate...
ver más
|
|
|
|
|
|
|
|
|
|
|
Haohui Lu and Shahadat Uddin
Artificial intelligence is changing the practice of healthcare. While it is essential to employ such solutions, making them transparent to medical experts is more critical. Most of the previous work presented disease prediction models, but did not explai...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yúri Faro Dantas de Sant?Anna, José Elwyslan Maurício de Oliveira and Daniel Oliveira Dantas
The lymphocyte classification problem is usually solved by deep learning approaches based on convolutional neural networks with multiple layers. However, these techniques require specific hardware and long training times. This work proposes a lightweight...
ver más
|
|
|
|
|
|
|
|
|
|
|
Igor S. Masich, Vadim S. Tyncheko, Vladimir A. Nelyub, Vladimir V. Bukhtoyarov, Sergei O. Kurashkin and Aleksey S. Borodulin
Logical analysis of data (LAD), an approach to data analysis based on Boolean functions, combinatorics, and optimization, can be considered one of the methods of interpretable machine learning. A feature of LAD is that, among many patterns, different typ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Charl Maree and Christian W. Omlin
Personalisation of products and services is fast becoming the driver of success in banking and commerce. Machine learning holds the promise of gaining a deeper understanding of and tailoring to customers? needs and preferences. Whereas traditional soluti...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xiaoyi Ge, Shuai Hao, Yuxiao Li, Bin Wei and Mingshu Zhang
Social media fake news has become a pervasive and problematic issue today with the development of the internet. Recent studies have utilized different artificial intelligence technologies to verify the truth of the news and provide explanations for the r...
ver más
|
|
|
|
|
|