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University news

Connecting you to the latest AI research and innovation

Stay up-to-date with the latest news from MBZUAI and the wider industry, featuring insights into ongoing University research, innovations, and developments shaping the future of artificial intelligence. The Node gathers expert commentary, press announcements, and initiatives from the University and its partners, keeping you informed on the most relevant trends and breakthroughs.

Results: 97 Tag: machine learning
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MBZUAI’s Robotics Program brings AI to the physical realm for robots that sense, act, and learn in the real world

Friday, 18 October, 2024

MBZUAI’s Robotics Program brings AI to the physical realm for robots that sense, act, and learn in the real world

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MBZUAI’s Robotics Program brings AI to the physical realm for robots that sense, act, and learn in the real world

Machine-learning-driven predictions for antimicrobial resistance could play a role in addressing looming global health crisis

Thursday, 17 October, 2024

Machine-learning-driven predictions for antimicrobial resistance could play a role in addressing looming global health crisis

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The new machine learning method can analyze electronic medical records and could help physicians identify patients who are at risk of AMR.

MBZUAI to showcase transformative AI-powered innovations at GITEX 2024

Friday, 11 October, 2024

MBZUAI to showcase transformative AI-powered innovations at GITEX 2024

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MBZUAI to showcase transformative AI-powered innovations at GITEX 2024

Mechanics and mimicry: Yoshihiko Nakamura’s journey in robotics

Thursday, 12 September, 2024

Mechanics and mimicry: Yoshihiko Nakamura’s journey in robotics

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Over the past five decades, Yoshihiko Nakamura has helped take robotics out of the realm of science fiction and into the world of beneficial application.

Orchestrated efficiency: A new technique to increase model efficiency during training

Wednesday, 14 August, 2024

Orchestrated efficiency: A new technique to increase model efficiency during training

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Presented at ICML 2024, Horváth's new study proposes a framework to efficiently train machine learning models for use in federated settings, where data is processed on user devices to ensure privacy.

The complexities of identifying causality in the real world: A new study presented at ICML

Saturday, 27 July, 2024

The complexities of identifying causality in the real world: A new study presented at ICML

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MBZUAI researchers and faculty presented a study at ICML that addresses one of the most fundamental problems in causal discovery.

New approaches for machine learning optimization presented at ICML

Wednesday, 24 July, 2024

New approaches for machine learning optimization presented at ICML

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MBZUAI research assistant Eduard Gorbunov co-authored the study in collaboration with scientists from seven other universities around the world.

More than meets the eye: Identifying hidden causal variables with causal representation learning

Tuesday, 23 July, 2024

More than meets the eye: Identifying hidden causal variables with causal representation learning

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A study presented at ICML by Kun Zhang proposes a new approach for identifying hidden causal variables based on observable data.

How computer vision model architecture and training affect performance

Monday, 22 July, 2024

How computer vision model architecture and training affect performance

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Zhiqiang Shen, assistant professor of machine learning at MBZUAI, discusses one of 25 studies being presented by MBZUAI researchers at ICML 2024.

Driving towards innovation: a visionary approach to traffic sign detection and recognition

Tuesday, 11 June, 2024

Driving towards innovation: a visionary approach to traffic sign detection and recognition

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Transportation expert Fatima Ahmed Alkhoori had already clocked up an impressive level experience when she applied to join MBZUAI to study for a master’s in ML back in 2022.

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