ASE 2023
Mon 11 - Fri 15 September 2023 Kirchberg, Luxembourg
Thu 14 Sep 2023 14:06 - 14:18 at Room C - Testing AI Systems 4

Unsupervised learning systems using clustering have gained significant attention for numerous applications due to their unique ability to discover patterns and structures in large unlabeled datasets. However, their effectiveness highly depends on their configuration, which requires domain-specific expertise and often involves numerous manual trials. Specifically, selecting appropriate algorithms and hyperparameters adds to the complexity of the configuration process. In this paper, we propose, apply, and assess an automated approach (AutoConf) for configuring unsupervised learning systems using clustering, leveraging metamorphic testing and Bayesian optimization. Metamorphic testing is utilized to verify the configurations of unsupervised learning systems by applying a series of input transformations. We use Bayesian optimization guided by metamorphic-testing output to automatically identify the optimal configuration. The approach aims to streamline the configuration process and enhance the effectiveness of unsupervised learning systems. It has been evaluated through experiments on six datasets from three domains for anomaly detection. The evaluation results show that our approach can find configurations outperforming the baseline approaches as they achieved a recall of 0.89 and a precision of 0.84 (on average).

Thu 14 Sep

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

13:30 - 15:00
Testing AI Systems 4Research Papers / NIER Track at Room C
13:30
12m
Talk
Mutation-based Fault Localization of Deep Neural NetworksACM Distinguished Paper
Research Papers
Ali Ghanbari Iowa State University, Deepak-George Thomas Dept. of Computer Science, Iowa State University, Muhammad Arbab Arshad Dept. of Computer Science, Iowa State University, Hridesh Rajan Iowa State University
Pre-print
13:42
12m
Talk
Fault Localization for Buggy Deep Learning Framework Conversions in Image Recognition
NIER Track
Nikolaos Louloudakis University of Edinburgh, Perry Gibson University of Glasgow, José Cano University of Glasgow, Ajitha Rajan University of Edinburgh
Pre-print File Attached
13:54
12m
Talk
Towards Safe Automated Refactoring of Imperative Deep Learning Programs to Graph Execution
NIER Track
Raffi Khatchadourian City University of New York (CUNY) Hunter College, Tatiana Castro Vélez City University of New York (CUNY) Graduate Center, Mehdi Bagherzadeh Oakland University, Nan Jia City University of New York (CUNY) Graduate Center, Anita Raja City University of New York (CUNY) Hunter College
Pre-print Media Attached File Attached
14:06
12m
Talk
AutoConf : Automated Configuration of Unsupervised Learning Systems using Metamorphic Testing and Bayesian Optimization
Research Papers
Lwin Khin Shar Singapore Management University, Arda Goknil SINTEF Digital, Erik Johannes Husom SINTEF Digital, Sagar Sen , Yan Naing Tun Singapore Management University, Kisub Kim Singapore Management University, Singapore
File Attached
14:18
12m
Talk
An Intentional Forgetting-Driven Self-Healing Method For Deep Reinforcement Learning SystemsRecorded talk
Research Papers
Ahmed Haj Yahmed École Polytechnique de Montréal, Rached Bouchoucha Polytechnique Montréal, Houssem Ben Braiek Polytechnique Montréal, Foutse Khomh Polytechnique Montréal
Pre-print Media Attached
14:30
12m
Talk
A Majority Invariant Approach to Patch Robustness Certification for Deep Learning ModelsRecorded talk
NIER Track
Qilin Zhou City University of Hong Kong, Zhengyuan Wei City University of Hong Kong, Hong Kong, Haipeng Wang City University of Hong Kong, Wing-Kwong Chan City University of Hong Kong, Hong Kong
Pre-print Media Attached