
Workshop on Energy Efficient Machine Learning & Cognitive Computing (EMC2) 2025
Descrição
This text provides an archive of calls for contributions to various conferences and workshops in computer architecture and high-performance computing. It invites submissions for papers, tutorials, and workshops, showcasing opportunities for researchers to share their work and collaborate on advancements in the field.
Destaques
Focus on energy-efficient machine learning and cognitive computing. Covers applications from mobile devices to large-scale data centers. Topics include neural network architectures, efficient hardware designs, and power-efficient memory architectures. Discussions on network reduction techniques, simulation, and emulation techniques for machine learning. Optimizations for training techniques, load balancing, and AI system challenges like verification and privacy. Keynotes, invited talks, and discussion panels by leading researchers. Peer-reviewed papers and independent publication through IEEE CPS. Aims to reduce the carbon footprint of AI through industry-academia collaboration. Includes computer vision, image processing, augmented/mixed reality, and more. Addresses performance, energy, reliability, accuracy, and security in AI systems.
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