
New Book by the INESC-ID researcher Andreas Wichert and his PhD student Luís Sá-Couto
World Scientific just published the work “Machine Learning — A Journey to Deep Learning”, written by INESC-ID researcher Andreas Wichert and his PhD student Luís Sá-Couto.
This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.
The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.
The book is available here.
About the authors:
Andreas Wichert studied computer science at the University of Saarland, where he graduated in 1993. Afterwards, he became a PhD student at the Department of Neural Information Processing, University of Ulm. Since 2006 he is Assistant Professor at Department of Computer Science and Engineering, University of Lisbon where he is as well lecturing about machine learning and quantum computation. His research focuses on neuronal networks, cognitive systems and quantum computation.
Luis Sa-Couto studied computer science at the Department of Computer Science and Engineering, University of Lisbon, where he graduated in 2018. Since then he is a PhD student under the supervision of Prof Andreas Wichert with the topic Extending Deep Learning Applicability Through Attention-inspired Networks for Object Recognition. He lectured practical classes in AI and machine learning.
Upcoming Events
Mathematics, Physics & Machine Learning Seminar Series (Online)

The Mathematics, Physics & Machine Learning seminar series has started on October 2020 and runs until March 2021.
The seminars aim to bring together mathematicians and physicists interested in machine learning (ML) with ML and AI experts interested in mathematics and physics, with the goal of introducing innovative Mathematics and Physics-inspired techniques in Machine Learning and, reciprocally, applying Machine Learning to problems in Mathematics and Physics.
Attendance is free but registration is required.
More information is available here.
International European Conference on Parallel and Distributed Computing

The 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021) will take from August 30 to September 3 2021 in Lisbon.
Euro-Par is the prime European conference covering all aspects of parallel and distributed processing, ranging from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-fledged applications, from architecture, compiler, language and interface design and implementation, to tools, support infrastructures, and application performance aspects.
The 2021 edition of Euro-Par will be organized as a collaboration between INESC-ID and Instituto Superior Técnico (IST).
Important Dates:
– Abstract Submission: February 5, 2021
– Paper Submission Deadline: February 12, 2021
– Author Notification: April 30, 2021
– Camera-Ready Papers: June 6, 2021
More information is available here.