Isidora Chara Tourni

Boston University | BU · Department of Computer Science

Deep learning models perform remarkably well for the same task under the assumption that data is always coming from the same distribution. However, this is generally violated in practice, mainly due to the differences in data acquisition techniques and the lack of information about the underlying source of new data. Domain generalization targets th...

News media structure their reporting of events or issues using certain perspectives. When describing an incident involving gun violence, for example, some journalists may focus on mental health or gun regulation, while others may emphasize the discussion of gun rights. Such perspectives are called "frames" in communication research. We study, for t...

Deep learning models perform remarkably well for the same task under the assumption that data is always coming from the same distribution. However, this is generally violated in practice, mainly due to the differences in the data acquisition techniques and the lack of information about the underlying source of new data. Domain Generalization target...

We conduct an empirical study of unsupervised neural machine translation (NMT) for truly low resource languages, exploring the case when both parallel training data and compute resource are lacking, reflecting the reality of most of the world's languages and the researchers working on these languages. We propose a simple and scalable method to impr...

The complexity of modern industrial processes and the constant innovations in production monitoring technologies and data collection, strongly outline the need for advancements in production data analysis. Data Mining is a rapidly growing field, aiming in understanding data and extracting previously unknown information, with the use of Machine Lear...