Results 51 to 60 of about 147,166 (261)

Hindsight Preference Learning for Offline Preference-based Reinforcement Learning

open access: yesCoRR
Offline preference-based reinforcement learning (RL), which focuses on optimizing policies using human preferences between pairs of trajectory segments selected from an offline dataset, has emerged as a practical avenue for RL applications. Existing works rely on extracting step-wise reward signals from trajectory-wise preference annotations, assuming ...
Chen-Xiao Gao   +4 more
openaire   +2 more sources

Pathways and pitfalls: a qualitative study of student experiences in biomedical science education

open access: yesFEBS Open Bio, EarlyView.
Biomedical science students from underrepresented backgrounds face barriers including financial strain, disrupted laboratory access and cultural exclusion. Peer networks provide vital support when institutional systems are difficult to navigate. To create inclusive learning environments and achieve academic success, educators should blend active, hands‐
Olivia J. Russell   +8 more
wiley   +1 more source

From patient advocacy to patient‐driven research: Building active partnerships beginning at the bench to reach the bedside

open access: yesFEBS Open Bio, EarlyView.
Research is strongest when conducted alongside patients, not just about them. Patient research organizations help integrate patient perspectives into research priorities, study design, and scientific meetings, leading to meaningful patient outcomes and development of relevant therapies.
Jenica H. Kakadia   +9 more
wiley   +1 more source

Learning Style Preferences Among Male and Female ESL Students in Universiti-Sains Malaysia

open access: yesJournal of Educators Online, 2015
Individuals preferentially process information in different ways. This includes the varied learning style preference of the individuals in any study program, including English as a Second Language (ESL).
Munir Shuib, Siti Norbaya Azizan
doaj  

Multi-Type Preference Learning: Empowering Preference-Based Reinforcement Learning with Equal Preferences

open access: yes2025 IEEE International Conference on Robotics and Automation (ICRA)
Preference-Based reinforcement learning (PBRL) learns directly from the preferences of human teachers regarding agent behaviors without needing meticulously designed reward functions. However, existing PBRL methods often learn primarily from explicit preferences, neglecting the possibility that teachers may choose equal preferences.
Ziang Liu 0019   +4 more
openaire   +4 more sources

Evaluating GenAI‐produced feedback on undergraduate bioscience essays against good higher education feedback practice

open access: yesFEBS Open Bio, EarlyView.
This pilot study investigates the potential of Generative AI to provide formative feedback to students. ChatGPT was prompted to provide feedback on Year 1 Bioscience essays, which were evaluated against established good feedback practices. GenAI‐authored feedback had useful elements, but was limited in scope. GenAI may have potential to provide instant,
Annabel Court   +3 more
wiley   +1 more source

Determinants of undergraduate bioscience engagement: Validating attendance barriers and classroom spatial behaviour across institutions

open access: yesFEBS Open Bio, EarlyView.
Student engagement extends beyond simple attendance. Across 891 bioscience students from three universities, attendance behaviour was associated mainly with structural influences, whereas classroom spatial behaviour reflected affective and sensory factors.
Nigel Page   +4 more
wiley   +1 more source

Risk preferences of learning algorithms

open access: yesGames and Economic Behavior
Agents' learning from feedback shapes economic outcomes, and many economic decision-makers today employ learning algorithms to make consequential choices. This note shows that a widely used learning algorithm, $\varepsilon$-Greedy, exhibits emergent risk aversion: it prefers actions with lower variance.
Andreas A. Haupt, Aroon Narayanan
openaire   +3 more sources

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio   +8 more
wiley   +1 more source

Early Clinical, Imaging, and Pathological Characteristics of SRPK3/TTN‐Digenic Myopathy

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective SRPK3/TTN‐digenic myopathy was recently established as a skeletal muscle myopathy caused by digenic inheritance. This study characterizes the early clinical presentation of SRPK3/TTN‐digenic myopathy in one previously reported and seven newly identified pediatric patients.
Rotem Orbach   +23 more
wiley   +1 more source

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