Agnik, the global leader of the vehicle analytics market, announced today that it is going to offer a wide range of Deep Machine Learning-based solutions for powering its new and existing products in ...

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its applications. Supervised learning is a type of Machine Learning which learns ...

The emergence of tools like ChatGPT complicates the ability of instructors to assess genuine learning, raising concerns about the future of this educational model. The COVID pandemic accelerated the ...

LOUISVILLE, Ky. (WDRB) -- Southern Indiana school districts that switched to eLearning Tuesday after several inches of snowfall had to change their eLearning plans after an internet outage briefly ...

Background: Critical thinking is a crucial skill in the nursing profession and must be fostered through nursing education. Simulation-based learning (SBL) with technological modalities is a ...

Ohio State may offer university-wide asynchronous classes on every federal general election day as part of an effort to encourage civic engagement if university leadership approves the resolution.

Abstract: Federated Learning is a distributed machine learning paradigm that enables model training across decentralized devices holding local data, thereby preserving data privacy and reducing the ...

Introduction: In online learning context, achievement emotions are of great significance and exert an influence on students’ learning performance. However, the research conclusions about the impact of ...

Reinforcement Learning RL is increasingly used to enhance LLMs, especially for reasoning tasks. These models, known as Large Reasoning Models (LRMs), generate intermediate “thinking” steps before ...

💫 Advancing Long-form Writing Capabilities: Our resulting writer models show that our RL framework largely improves long-form writing performance over strong SFT baselines. 💫 Generalization from ...

Abstract: Semi-asynchronous federated learning (SAFL) leverages the benefits of synchronous and asynchronous updates, effectively addressing the straggling effect caused by heterogeneity among clients ...