Results 11 to 20 of about 8,972,433 (325)
A Survey on Bias and Fairness in Machine Learning [PDF]
ACM Computing Surveys, 2019 With the widespread use of artificial intelligence (AI) systems and applications in our everyday lives, accounting for fairness has gained significant importance in designing and engineering of such systems.
Ninareh Mehrabi +4 more
semanticscholar +1 more source
Machine Learning: Algorithms, Real-World Applications and Research Directions
SN Computer Science, 2021 In the current age of the Fourth Industrial Revolution (4IR or Industry 4.0), the digital world has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data, business data, social media data, health data, etc.
Iqbal H. Sarker
semanticscholar +1 more source
Membership Inference Attacks Against Machine Learning Models [PDF]
IEEE Symposium on Security and Privacy, 2016 We quantitatively investigate how machine learning models leak information about the individual data records on which they were trained. We focus on the basic membership inference attack: given a data record and black-box access to a model, determine if ...
R. Shokri +3 more
semanticscholar +1 more source
Mathematics, 2023 Considering the worst-case scenario, the junction-tree algorithm remains the most general solution for exact MAP inference with polynomial run-time guarantees.
Alexander Bauer +2 more
doaj +1 more source
Entropy, 2023 We explore unique considerations involved in fitting machine learning (ML) models to data with very high precision, as is often required for science applications. We empirically compare various function approximation methods and study how they scale with increasing parameters and data.
Eric J. Michaud, Ziming Liu, Max Tegmark
openaire +5 more sources
Machine learning classification–Regression schemes for desert locust presence prediction in western Africa [PDF]
, 2023 Producción CientíficaFor decades, humans have been confronted with numerous pest species, with the desert locust being one of the most damaging and having the greatest socio-economic impact.
Casanova Mateo, Carlos +4 more
core +1 more source
Quantum machine learning [PDF]
Nature, 2017 Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Since quantum systems produce counter-intuitive patterns believed not to be efficiently produced by classical systems, it is reasonable to postulate that quantum computers may outperform classical computers
Seth Lloyd +6 more
openaire +6 more sources
Scientific Reports, 2022 Proteins perform many essential functions in biological systems and can be successfully developed as bio-therapeutics. It is invaluable to be able to predict their properties based on a proposed sequence and structure. In this study, we developed a novel
Zichen Wang +10 more
doaj +1 more source
Practical Black-Box Attacks against Machine Learning [PDF]
ACM Asia Conference on Computer and Communications Security, 2016 Machine learning (ML) models, e.g., deep neural networks (DNNs), are vulnerable to adversarial examples: malicious inputs modified to yield erroneous model outputs, while appearing unmodified to human observers. Potential attacks include having malicious
Nicolas Papernot +5 more
semanticscholar +1 more source
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose A set of treatment planning strategies were designed and retrospectively implemented for locally advanced, non‐small cell lung cancer (NSCLC) patients in order to minimize cardiac dose without compromising target coverage goals. Methods Retrospective analysis was performed for 20 NSCLC patients prescribed to 60–66 Gy that received a ...
Joshua P. Kim +5 more
wiley +1 more source