Education Week

A New National Effort Aims to Spread Learning Beyond School Walls

It takes a village to prepare students for a changing workforce, build civic engagement, and help educators solve big ...
UroToday

Semi-supervised learning in prostate MRI tumor detection approaches fully supervised performance on external validation.

To evaluate the diagnostic performance of semi-supervised learning models for aggressive prostate cancer detection on MRI compared to fully supervised models trained with additional expert annotations ...
Carson-Newman University

Active Learning vs. Passive Learning: Why It Matters For Online Students

If you’ve ever finished an online lecture and realized you barely remember what was covered, you’ve experienced the difference between active vs. passive learning. In virtual classrooms, it’s easy to ...
IEEE

IDALC: A Semi-Supervised Framework for Intent Detection and Active Learning based Correction

Abstract: Voice-controlled dialog systems have become immensely popular due to their ability to perform a wide range of actions in response to diverse user queries. These agents possess a predefined ...
GitHub

Solving Semi-Supervised Few-Shot Learning

We investigate the failures of representative semi-supervised learning methods, e.g., FixMatch and DebiasPL, in the challenging few-shot setup for finetuning a pretrained VLM. Our analyses reveal the ...
GitHub

TRAPO: A Semi-Supervised Reinforcement Learning Framework for Boosting LLM Reasoning.

TraPO is a semi-supervised reinforcement learning framework that bridges unlabeled and labeled samples for training large reasoning models (LRMs). Built upon GRPO, TraPO leverages a small set of ...
IEEE

Specific Emitter Identification Based on Semi-Supervised Active Learning

Abstract: Specific emitter identification (SEI) plays a critical role in the security and management of communication systems, particularly within the context of instrumentation and the Internet of ...
Frontiers

OpenLabCluster: active learning based clustering and classification of animal behaviors based on kinematic body keypoints

Quantifying natural behavior from video recordings is a key component in ethological studies. Markerless pose estimation methods have provided an important step toward that goal by automatically ...
marktechpost

A Coding Guide to Master Self-Supervised Learning with Lightly AI for Efficient Data Curation and Active Learning

In this tutorial, we explore the power of self-supervised learning using the Lightly AI framework. We begin by building a SimCLR model to learn meaningful image representations without labels, then ...
Case Western Reserve University

Experiential Learning

Learning results from what the student does and thinks and only from what the student does and thinks. The teacher can advance learning only by influencing what the student does to learn. (Lovett et ...