IAL 2021
Interactive Adaptive Learning 2021

Table of Contents

• Front Matter
  
• Preface
  Summary: There were 13 papers submitted for peer-review to this workshop. Out of these, 10 papers were accepted for this volume.
• Table of Contents
  

Research Papers

• MetaREVEAL: RL-based Meta-learning from Learning Curves 1-20
  Manh Hung Nguyen, Isabelle Guyon, Lisheng Sun-Hosoya, Nathan Grinsztajn
• Uncertainty and Utility Sampling with Pre-Clustering 21-34
  Zhixin Huang, Yujiang He, Stephan Vogt, Bernhard Sick
• Evidential Nearest Neighbours in Active Learning 35-49
  Daniel Zhu, Arnaud Martin, Yolande Le Gall, Jean-Christophe Dubois, Vincent Lemaire
• SLAYER: A Semi-supervised Learning Approach for Drifting Data Streams under Extreme Verification Latency 50-64
  Maria Arostegi, Jesus Lobo, Javier Del Ser
• A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving 65-69
  Maarten Bieshaar, Marek Herde, Denis Huselijc, Bernhard Sick
• Active Class Selection with Uncertain Class Proportions 70-79
  Mirko Bunse, Katharina Morik
• Sample Noise Impact on Active Learning 80-88
  Alexandre Abraham, Léo Dreyfus-Schmidt
• Contrastive Representations for Label Noise Require Fine-Tuning 89-104
  Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
• Combining Gaussian Processes with Neural Networks for Active Learning in Optimization 105-120
  Jiří Růžička, Jan Koza, Jiří Tumpach, Zbyněk Pitra, Martin Holena
• Stochastic Adversarial Gradient Embedding for Active Domain Adaptation 121-137
  Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami, Hudelot Céline