A new study from the University at Albany shows that artificial intelligence systems may organize information in far more ...
Think your cerebellum only coordinates fluid movements? New 2026 research reveals how your "little brain" also creates the ...
Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...
Background Anxiety disorders are persistent, functionally impairing conditions with high societal burden. In contrast, ...
Abstract: Training neural networks (NNs) to behave as model predictive control (MPC) algorithms is an effective way to implement them in constrained embedded devices. By collecting large amounts of ...
Massive computing systems are required to train neural networks. The prodigious amount of consumed energy makes the creation of AI applications significant polluters ...
Zeroth-order Optimization (ZO) has received wide attention in machine learning, especially when computing full gradient is expensive or even impossible. Recently, ZO has emerged as an important ...
Abstract: Recent advancements in deep neural networks heavily rely on large-scale labeled datasets. However, acquiring annotations for large datasets can be challenging due to annotation constraints.
1 School of Mechanical Engineering, Vellore Institute of Technology, Chennai, India 2 Centre for e-Automation Technologies, Vellore Institute of Technology, Chennai, India Introduction: Friction Stir ...
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