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 ...

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 ...

Copyright (c) 2020 Arduino SA. All rights reserved. This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General ...

Machine learning algorithms are often categorized as lazy learners or eager learners based on how they learn and make predictions. Among these, the K-Nearest Neighbor (KNN) algorithm stands out as a ...

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 ...

1 Laboratory of Computer Engineering, Data Science and Artificial Intelligence, National Higher Polytechnic School of Douala, Douala, Cameroon. 2 Mobile Computing and Networking Research Laboratory, ...

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 ...

In the realm of e-commerce, personalized recommendations are a crucial component in enhancing user experience and optimizing sales efficiency. To address the inherent sparsity challenge prevalent in ...

K-Nearest Neighbors (KNN) is a simple yet effective supervised machine learning algorithm used for both regression and classification tasks. The algorithm works by finding the K nearest data points in ...