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Gathering labeled data to train well-performing machine learning models is one of the critical challenges in many applications. Active learning aims at red
Recent studies have shown that vision transformer (ViT) models can attain better results than most state-of-the-art convolutional neural networks (CNNs) across various image recognition tasks, and can do so while using considerably fewer computational resources. This has led some researchers to propose ViTs could replace CNNs in this field.However, despite their promising performance, ViTs areContinue Reading
Principal component analysis(PCA) is one of the key algorithms that are part of any machine learning curriculum. Initially created in the early 1900s, PCA is a fundamental algorithm to understand…
A research team from McGill University, Université de Montréal, DeepMind and Mila presents an end-to-end, model-based deep reinforcement learning (RL) agent that dynamically attends to relevant parts of its environments to facilitate out-of-distribution (OOD) and systematic generalization.
In a broader mathematical or computational perspective, an optimization problem is defined as a problem of finding the best solution from all feasible solutions. In terms of Machine Learning and…
M. Lindvall, und J. Molin. (2020)cite arxiv:2001.07455Comment: Accepted for presentation in poster format for the ACM CHI'19 Workshop <Emerging Perspectives in Human-Centered Machine Learning>.