Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
Non-terrestrial networks have their own challenges that cellular networks didn't have. Will AI help solve them dynamically?
Abstract: The controller placement problem and controller selection problem are two major issues that, if not considered seriously, lead to high network costs, load unbalancing, and high latency. To ...
From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Machine learning systems embed preferences either in training losses or through post-processing of calibrated predictions. Applying information design methods from Strack and Yang (2024), this paper ...
A new peer-reviewed study published in the journal Algorithms signals a major shift in how humanitarian logistics can be ...
Achieving precise and predictable motion remains a persistent challenge for microelectromechanical systems (MEMS), where many actuators respond ...
XRP has lost some steam over the past twenty-four hours as the Senate delayed a key crypto market structure bill on January 15. At the same time, daily trading volume slipped 30% as the broader market ...
We are excited to inform you that the current Machine Learning: Theory and Hands-On Practice with Python Specialization (taught by Professor Geena Kim) is being retired and will be replaced with a new ...
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