We propose a framework using contrastive learning as a pre-training task to perform image classification in the presence of noisy labels. Recent strategies, such as pseudo-labelling, sample selection with Gaussian Mixture models, and weighted supervised contrastive learning have been combined into a fine-tuning phase following the pre-training.
Continue readingThis paper explains our participation in task 1of the CASE 2021 shared task. This task is about multilingual event extraction from the news. We focused on sub-task 4, event information extraction. This sub-task has a small training dataset, and we fine-tuned a multilingual BERT to solve this sub-task.
Continue readingWe are very proud of our research director Sabri Skhiri for joining the program committee of IEEE Big Data 2021!
He will be the only Belgian and one of the few Europeans to be on the program committee of this top tier research conference in Big Data.
Congratulation Sabri!
Continue readingThe General Data Protection Regulation (GDPR) requires data controllers to implement end-to-end compliance. Controllers must therefore ensure that the terms agreed with the data subject and their own obligations under GDPR are respected in the data flows from data subject to controllers, processors and sub-processors (i.e. data supply chain).
Continue readingCongratulations to our research director Sabri Skhiri on his appointment as industry co-chair of the international conference on distributed and event-based systems.
Continue readingThe assessment of the digital transformation progress is essential to understand and undertake in order to evaluate the level of maturity of data-driven companies in terms of data capabilities and to plan for improvement actions.
Continue readingMaturity models are helpful business tools that refine and develop how organizations conduct their businesses and benchmark their maturity status against a scale or with industry peers. They serve to prioritize the actions for improvement better and control the progress in reaching the target maturity stage.
Continue readingIn this paper, we propose a framework for image classification tasks, named MIC, that takes as input multi-view images, such as RGB-T images for surveillance purposes. We combine auto-encoder and generative adversarial network architectures to ensure the multi-view embedding in a common latent space.
Continue readingAfter the success of five international workshops co-located at IEEE Big Data, the MDPI Data Journal is dedicating a special issue to real-time stream analytics, stream mining, CER/CEP and stream data management in big data.
Continue readingFor safety-critical systems involving AI components (such as in planes, cars, or healthcare), safety and associated certification tasks are one of the main challenges, which can become costly and difficult to address.
One key aspect is to ensure that the decisions a machine-learning classifier makes are properly calibrated.
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