Within the context of text-as-data paradigm, new type of analysis and metrics are today available to the political science research, allowing new and different scientific approaches. Political science is an area particularly benefited with this new paradigm. Traditionally, all national … Read More
S9 (2017-2018)
Generative Modelling of Single-cell Transcriptomic Data
Single-cell sequencing technology holds the promise of unravelling cell heterogeneities hidden in ubiquitous bulk-level analyses. However, limitations of current experimental methods pose new obstacles that prevent accurate conclusions from being drawn. To overcome this, researchers have developed computational methods which … Read More
Hotel Bookings Cancellation Prediction
Booking cancellations contribute negatively to the production of accurate forecasts, a critical tool in the hospitality industry. To lessen this influence, hotels implement rigid cancellation policies and overbooking strategies, which in turn can negatively impact revenue and the hotel’s social … Read More
Two optimisation ideas for locating a target
We want to guess the position of a target, based only on how weakly or strongly its emitted wireless signal is received at a few places. Assuming usual probabilistic properties of wireless channels, we proceed to frame this problem as … Read More
From genetic data to actionable knowledge
Genetic testing has long been a major promise to foster personalized healthcare and personalized wellness. The major barrier to its success and massification is the gap between getting the genetic data and providing actionable advice, alongside the high cost of … Read More
Wikipedia Graph Mining: Dynamic structure of collective memory
Wikipedia is the biggest encyclopedia ever created and the fifth most visited website in the world. Tens of millions of people surf it every day, seeking answers to various questions. Collective user activity on its pages leaves publicly available footprints … Read More
Exploring Medical Records with Machine Learning and Natural Language Processing
We will present an ongoing project at Priberam that covers aspects that go from the definition of ontologies, corpus gathering and annotation criteria to the concrete annotation task, and finally the development of an engine that automatically extracts, labels and … Read More
Deep Learning Applied to Medical Imaging
The seminar will be a brief overview of deep learning techniques for semantic segmentation of images. Then, it will show a use case of deep learning usage for semantic segmentation of ischemic stroke lesions using 3D MRI data.
Kernel and Moment Based Prediction and Planning
In this talk I will introduce a combination of moment based predictive models with deep reinforcement learning architectures, Recurrent Predictive State Policy (RPSP) networks. Predictive state serves as an equivalent representation of a belief state. Therefore, the policy component of … Read More
Data Science, Machine Learning and AI: an IBM perspective
Since the first perceptron was implemented in an IBM 7042 to the success of Deep Blue against a human opponent and, more recently, IBM Watson’s victory on Jeopardy!, IBM has been intimately involved with the advancement of cognitive systems. With … Read More