Results 121 to 130 of about 476,790 (313)
Beyond Supervised Representation Learning
, 2019 The complexity of any information processing task is highly dependent on the space where data is represented. Unfortunately, pixel space is not appropriate for the computer vision tasks such as object classification.
Noroozi, Mehdi
core
Self-Supervised Lie Algebra Representation Learning via Optimal Canonical Metric
Learning discriminative representation with limited training samples is emerging as an important yet challenging visual categorization task. While prior work has shown that incorporating self-supervised learning can improve performance, we found that the
Yu, Xiaohan +3 more
core +1 more source
Intelligent Tutoring Systems for Adult Learning in STEM Disciplines
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Intelligent tutoring systems (ITS) are reshaping adult learning in STEM by providing adaptive, data‐driven instruction across classrooms, workplaces, and informal environments. In the context of ITS, this article compares generative AI, which creates personalized explanations and practice materials, with explainable AI, which focuses on ...
Jill Zarestky, Amanda R. Lager Gleason
wiley +1 more source
Joint discriminative representation learning for end-to-end person search
, 2023 Person search simultaneously detects and retrieves a query person from uncropped scene images. Existing methods are either two-step or end-to-end. The former employs two standalone models for the two sub-tasks, while the latter conducts person search ...
Xiaohan Yu +11 more
core +1 more source
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Mental well‐being is central to adult learner success, yet many adult education institutions lack capacity to provide timely and accessible support. This article examines how artificial intelligence (AI) can strengthen mental health–adjacent supports in adult and continuing higher education, with attention to professional practice and ...
Adam L. McClain, Thomas Wade
wiley +1 more source
Learning sparse representations in reinforcement learning
CoRR, 2019 Reinforcement learning (RL) algorithms allow artificial agents to improve their selection of actions to increase rewarding experiences in their environments. Temporal Difference (TD) Learning -- a model-free RL method -- is a leading account of the midbrain dopamine system and the basal ganglia in reinforcement learning.
Jacob Rafati, David C. Noelle
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi +2 more
wiley +1 more source
Representation Learning with Multisets
CoRR, 2019 Under review as a conference paper at ICLR 2020.
openaire +2 more sources
Meta-Learning Representations for Continual Learning
CoRR, 2019 A continual learning agent should be able to build on top of existing knowledge to learn on new data quickly while minimizing forgetting. Current intelligent systems based on neural network function approximators arguably do the opposite---they are highly prone to forgetting and rarely trained to facilitate future learning.
Khurram Javed, Martha White
openaire +3 more sources
Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler +20 more
wiley +1 more source