CAIN 2022
Mon 16 - Tue 17 May 2022
co-located with ICSE 2022
Mon 16 May 2022 08:27 - 08:30 at CAIN main room - Posters Chair(s): Helena Holmström Olsson, Iva Krasteva

Active learning is an established technique to reduce the labeling cost for building high-quality machine learning models. However, state-of-the-art approaches focus on maximizing the clean performance (e.g. accuracy) but disregarding robustness. In this work, we propose Robust Active Learning, an active learning process that integrates adversarial training – the most established method to produce robust models. First, we conduct an empirical study to evaluate the effectiveness of existing approaches and uncover the characteristics of data. Then, we propose a novel approach, density-based robust sampling with entropy (DRE), to target both clean performance and robustness. Our experiments are conducted on 11 acquisition functions, 4 datasets, 6 DNN architectures, and 15105 trained DNNs.

Mon 16 May

Displayed time zone: Eastern Time (US & Canada) change

07:45 - 09:15
PostersCAIN 2022 at CAIN main room
Chair(s): Helena Holmström Olsson Malmö University, Iva Krasteva Sofia University, GATE Institute
07:45
30m
Other
Activity: Networking Shuffle
CAIN 2022

08:15
3m
Poster
MLOps: Five Steps to Guide its Effective ImplementationPoster
CAIN 2022
08:18
3m
Poster
Towards A Methodological Framework for Production-ready AI-based Software ComponentsPoster
CAIN 2022
Markus Haug University of Stuttgart, Institute of Software Engineering, Empirical Software Engineering Group, Justus Bogner University of Stuttgart, Institute of Software Engineering, Empirical Software Engineering Group
08:21
3m
Poster
Preliminary Insights to enable automation of the Software Development Process in Software StartUps. A Investigation Study from the use of Artificial Intelligence and Machine LearningPoster
CAIN 2022
Olimar Borges PUCRS University, Valentina Lenarduzzi University of Oulu, Rafael Prikladnicki School of Technology at PUCRS University
08:24
3m
Poster
Identification of Out-of-Distribution Cases of CNN using Class-Based Surprise AdequacyPoster
CAIN 2022
Mira Marhaba Polytechnique Montreal, Ettore Merlo Polytechnique Montreal, Foutse Khomh Polytechnique Montréal, Giuliano Antoniol Polytechnique Montréal
08:27
3m
Poster
Robust Active Learning: Sample-Efficient Training of Robust Deep Learning ModelsPoster
CAIN 2022
Yuejun GUo Interdisciplinary Centre for Security, Qiang Hu University of Luxembourg, Maxime Cordy University of Luxembourg, Luxembourg, Mike Papadakis University of Luxembourg, Luxembourg, Yves Le Traon University of Luxembourg, Luxembourg
08:30
3m
Poster
A New Approach for Machine Learning Security Risk AssessmentPoster
CAIN 2022
Jun Yajima Fujitsu Limited, Maki Inui Fujitsu Limited, Takanori Oikawa Fujitsu Limited, Fumiyoshi Kasahara Fujitsu Limited, Ikuya Morikawa Fujitsu Limited, Nobukazu Yoshioka Waseda University, Japan
File Attached
08:33
3m
Poster
TopSelect: A Topology-based Feature Selection Method for Industrial Machine LearningPoster
CAIN 2022
Hadil Abukwaik ABB Corporate Research, Lefter Sula ABB Corporate Research Center, Pablo Rodriguez ABB
08:36
3m
Poster
Pynblint: a Static Analyzer for Python Jupyter NotebooksPoster
CAIN 2022
Luigi Quaranta University of Bari, Italy, Fabio Calefato University of Bari, Filippo Lanubile University of Bari
Pre-print File Attached
08:39
3m
Poster
Traceable Business-to-Safety Analysis Framework for Safety-critical Machine Learning SystemsPoster
CAIN 2022
Jati Hiliamsyah Husen Waseda University, Hironori Washizaki Waseda University, Hnin Tun Waseda University, Nobukazu Yoshioka Waseda University, Japan, Hironori Takeuchi Musashi University, Yoshiaki Fukazawa Waseda University
Media Attached File Attached
08:42
3m
Poster
Structural Causal Models as Boundary Objects in AI System DevelopmentPoster
CAIN 2022
Hans-Martin Heyn University of Gothenburg & Chalmers University of Technology, Eric Knauss Chalmers | University of Gothenburg
08:45
30m
Other
Poster Visits
CAIN 2022


Information for Participants
Mon 16 May 2022 07:45 - 09:15 at CAIN main room - Posters Chair(s): Helena Holmström Olsson, Iva Krasteva
Info for room CAIN main room:

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