Stan Matwin

Improving the Interpretability of Deep Neural Networks with Knowledge Distillation

2018

Deep Neural Networks have achieved huge success at a wide spectrum of applications from language modeling, computer vision to speech recognition. However, nowadays, good performance alone is not enough to satisfy the needs of practical …

SemEval-2020 Task 5: Counterfactual Recognition

2020

We present a counterfactual recognition (CR) task, the shared Task 5 of SemEval-2020. Counterfactuals describe potential outcomes (consequents) produced by actions or circumstances that did not happen or cannot happen and are counter to the …

Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing 2017co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017)

2017 · HAL (Le Centre pour la Communication Scientifique Directe)

International audience

Evolutionary Augmentation Policy Optimization for Self-Supervised Learning

2023 · Advances in Artificial Intelligence and Machine Learning

Self-supervised Learning (SSL) is a machine learning algorithm for pretraining Deep Neural Networks (DNNs) without requiring manually labeled data. The central idea of this learning technique is based on an auxiliary stage aka pretext task …