Results 81 to 90 of about 16,800,197 (383)
Deep Reinforcement Learning using Cyclical Learning Rates [PDF]
arXiv, 2020 Deep Reinforcement Learning (DRL) methods often rely on the meticulous tuning of hyperparameters to successfully resolve problems. One of the most influential parameters in optimization procedures based on stochastic gradient descent (SGD) is the learning rate.
arxiv
Leading Learning & Development (L&D): ELE Leader Members Test-Drive Josh Bersin Academy [PDF]
, 2022 ELE would like to recruit members to create a 5-week cohort to experience semi-synchronous collaborative learning. As learning professionals, we’re faced with a largely new landscape and increasing demand for our work, as organizations begin to see why ...
Busby, Richard D +3 more
core +1 more source
FEBS Open Bio, EarlyView.This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi +2 more
wiley +1 more source
A Learning Algorithm for Relational Logistic Regression: Preliminary Results [PDF]
arXiv, 2016 Relational logistic regression (RLR) is a representation of conditional probability in terms of weighted formulae for modelling multi-relational data. In this paper, we develop a learning algorithm for RLR models. Learning an RLR model from data consists of two steps: 1- learning the set of formulae to be used in the model (a.k.a.
arxiv
Positive semidefinite support vector regression metric learning [PDF]
arXiv, 2020 Most existing metric learning methods focus on learning a similarity or distance measure relying on similar and dissimilar relations between sample pairs. However, pairs of samples cannot be simply identified as similar or dissimilar in many real-world applications, e.g., multi-label learning, label distribution learning.
arxiv
To learn and not to learn – that is the question
Procedia - Social and Behavioral Sciences, 2011 AbstractProblem StatementForms of examination in a Higher Educational setting. Existing practice often lacks the connection between learning processes that are deeper and reflective to their character. It is also usually focused on the individual and therefore fails to meet collaborative learning practice.
Maria Gustavson, Ellinor Silius-Ahonen
openaire +2 more sources
Mapping Hsp104 interactions using cross‐linking mass spectrometry
FEBS Open Bio, EarlyView.This study examines how cross‐linking mass spectrometry can be utilized to analyze ATP‐induced conformational changes in Hsp104 and its interactions with substrates. We developed an analytical pipeline to distinguish between intra‐ and inter‐subunit contacts within the hexameric homo‐oligomer and discovered contacts between Hsp104 and a selected ...
Kinga Westphal +3 more
wiley +1 more source
5. Serial Team Teaching and the Evolving Scholarship of Learning: Students’ Perspective
Collected Essays on Learning and Teaching, 2011 Faculty and students at the University of Toronto were surveyed and interviewed to form a case study of serial team teaching, in which multiple instructors take turns teaching a segment of the same course in sequence.
Melody Neumann +12 more
doaj +1 more source
Meta-SGD: Learning to Learn Quickly for Few-Shot Learning [PDF]
arXiv, 2017 Few-shot learning is challenging for learning algorithms that learn each task in isolation and from scratch. In contrast, meta-learning learns from many related tasks a meta-learner that can learn a new task more accurately and faster with fewer examples, where the choice of meta-learners is crucial.
arxiv
Designing professional learning [PDF]
The Designing Professional Learning report provides a snapshot of the key elements involved in creating effective and engaging professional learning in a globally dispersed market.
Learning Forward
core