main webpage W Topic Artificial Intelligence arXiv (Cornell University) Virtual Node Tuning for Few-shot Node Classification 2023 Few-shot Node Classification (FSNC) is a challenge in graph representation learning where only a few labeled nodes per class are available for training. To tackle this issue, meta-learning has been proposed to transfer structural knowledge from base classes w… Article Open Artificial Intelligence Open Article Page

Artificial Intelligence

Intelligence of machines Artificial intelligence ( AI ) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Alexa); autonomous vehicles (e.g., Waymo); generative and creative tools (e.g. Critical Symbolic Virtual Narrative Open Artificial Intelligence Open Article Page

Exploring foci of: arXiv (Cornell University) Virtual Node Tuning for Few-shot Node Classification 2023 Few-shot Node Classification (FSNC) is a challenge in graph representation learning where only a few labeled nodes per class are available for training. To tackle this issue, meta-learning has been proposed to transfer structural knowledge from base classes with abundant labels to target novel classes. However, existing solutions become ineffective or inapplicable when base classes have no or limited labeled nodes. To address this challenge, we propose an innovative method dubbed Virtual Node Tuning (VNT). Our app… Open Article Page

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Explore Artificial Intelligence W Topic Artificial Intelligence arXiv (Cornell University) Virtual Node Tuning for Few-shot Node Classification 2023 Few-shot Node Classification (FSNC) is a challenge in graph representation learning where only a few labeled nodes per class are available for training. To tackle this issue, meta-learning has been proposed to transfer structural knowledge from base classes w… Article Critical Symbolic Virtual Narrative Open Artificial Intelligence Open Article Page