Abstract: In multi-instance multi-label learning (i.e. MIML), each example is not only represented by multiple instances but also associated with multiple labels. Most existing algorithms solve MIML ...

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Deep Learning-based embeddings are used widely for “dense retrieval” in information retrieval, computer vision, NLP, amongst others, owing to capture diverse types of semantic information. This ...

Abstract: An adaptive k-nearest neighbor algorithm (AdaNN) is brought forward in this paper to overcome the limitation of the traditional k-nearest neighbor algorithm (kNN) which usually identifies ...

Recommender systems are essential in e-commerce for assisting users in navigating large product catalogs, particularly in visually driven domains like fashion. Traditional keyword-based systems often ...

Blocking is a canonical technique that groups records into blocks based on some key so that only items within the same block are compared. Effective blocking dramatically cuts comparisons while still ...

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As we progress into 2025, Artificial Intelligence (AI) continues to reshape industries and revolutionize how we interact with technology. For those starting their journey in AI, it’s essential to ...

Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects simply to a non-technical, business audience. Over… Supervised learning ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...