Abstract: Over the past decades, extensive research has been conducted on adversarial attacks and defense mechanisms in deep learning, particularly in real-world applications such as autonomous ...
High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
Mikel Hernaez receives funding from the Spanish Ministry of Science, Innovation and Universities, the government of Navarra, the EU Department of Defence, the Carlos III Health Institute and the ...
WASHINGTON — Lockheed Martin is launching a new initiative called “AI Fight Club,” a virtual battleground where companies can test their artificial intelligence algorithms for use in military ...
Abstract: Dynamic constrained multiobjective optimization problems (DCMOPs) are widely existed in real-world applications and emerged as a prominent research focus in the evolutionary computation ...
Panelists discuss how treatment goals for intermediate-risk myelofibrosis patients focus on achieving meaningful clinical outcomes including relieving symptoms, preventing worsening of anemia, ...
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