Workshop: Learning Representations with Limited Supervision

at IEEE BigData 2025, December 8–11, 2025 — Macau, China

Overview

This workshop explores cutting-edge techniques in representation learning with minimal labels. It welcomes contributions on self-supervised learning, transfer learning, in-context learning, and applications to domains with limited labeled data such as underwater and medical imaging.

Program Chair

Shaif Chowdhury, Baylor University

Presentation Schedule

Date: December 08
Session: Afternoon, 2–4 PM
Timezone: American/Chicago

Time Topic / Paper
2:00 PM Introduction
2:10 PM Few-Shot Learning with Pretrained Visual Embeddings of Eye-Tracking Patterns for Autism Detection
2:30 PM Residual GRU+MHSA: A Lightweight Hybrid Recurrent–Attention Model for Cardiovascular Disease Detection