|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
Vidhya Kamakshi and Narayanan C. Krishnan
Explainable Artificial Intelligence (XAI) has emerged as a crucial research area to address the interpretability challenges posed by complex machine learning models. In this survey paper, we provide a comprehensive analysis of existing approaches in the ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ezekiel Bernardo and Rosemary Seva
Explainable Artificial Intelligence (XAI) has successfully solved the black box paradox of Artificial Intelligence (AI). By providing human-level insights on AI, it allowed users to understand its inner workings even with limited knowledge of the machine...
ver más
|
|
|
|
|
|
|
|
|
|
|
Varada Vivek Khanna, Krishnaraj Chadaga, Niranajana Sampathila, Srikanth Prabhu, Venkatesh Bhandage and Govardhan K. Hegde
Polycystic Ovary Syndrome (PCOS) is a complex disorder predominantly defined by biochemical hyperandrogenism, oligomenorrhea, anovulation, and in some cases, the presence of ovarian microcysts. This endocrinopathy inhibits ovarian follicle development ca...
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
|
|
|
|
|
|
|
|
|
|
|
Jeonggeun Jo, Jaeik Cho and Jongsub Moon
Artificial intelligence (AI) is increasingly being utilized in cybersecurity, particularly for detecting malicious applications. However, the black-box nature of AI models presents a significant challenge. This lack of transparency makes it difficult to ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Michelle P. Banawan, Jinnie Shin, Tracy Arner, Renu Balyan, Walter L. Leite and Danielle S. McNamara
Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies, and similarities i...
ver más
|
|
|
|
|
|
|
|
|
|
|
Genane Youness and Adam Aalah
Prognosis and health management depend on sufficient prior knowledge of the degradation process of critical components to predict the remaining useful life. This task is composed of two phases: learning and prediction. The first phase uses the available ...
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
|
|
|
|
|
|